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• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

• Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

• Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
• Gives researchers the chance to collect information on why one strategy might be chosen over another
• Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

• It cannot necessarily be generalized to the larger population
• Cannot demonstrate cause and effect
• It may not be scientifically rigorous
• It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

• Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
• Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
• Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

• Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
• Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
• Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
• Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
• Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
• Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

• Archival records : Census records, survey records, and name lists are examples of archival records.
• Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
• Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
• Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
• Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
• Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

• Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
• Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
• Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
• Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

• Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
• Read examples of case studies to gain an idea about the style and format.
• Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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• Knowledge Base
• Methodology
• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Prevent plagiarism, run a free check.

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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McCombes, S. (2023, January 30). Case Study | Definition, Examples & Methods. Scribbr. Retrieved 15 April 2024, from https://www.scribbr.co.uk/research-methods/case-studies/

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Designing and Conducting Case Studies

This guide examines case studies, a form of qualitative descriptive research that is used to look at individuals, a small group of participants, or a group as a whole. Researchers collect data about participants using participant and direct observations, interviews, protocols, tests, examinations of records, and collections of writing samples. Starting with a definition of the case study, the guide moves to a brief history of this research method. Using several well documented case studies, the guide then looks at applications and methods including data collection and analysis. A discussion of ways to handle validity, reliability, and generalizability follows, with special attention to case studies as they are applied to composition studies. Finally, this guide examines the strengths and weaknesses of case studies.

Definition and Overview

Case study refers to the collection and presentation of detailed information about a particular participant or small group, frequently including the accounts of subjects themselves. A form of qualitative descriptive research, the case study looks intensely at an individual or small participant pool, drawing conclusions only about that participant or group and only in that specific context. Researchers do not focus on the discovery of a universal, generalizable truth, nor do they typically look for cause-effect relationships; instead, emphasis is placed on exploration and description.

Case studies typically examine the interplay of all variables in order to provide as complete an understanding of an event or situation as possible. This type of comprehensive understanding is arrived at through a process known as thick description, which involves an in-depth description of the entity being evaluated, the circumstances under which it is used, the characteristics of the people involved in it, and the nature of the community in which it is located. Thick description also involves interpreting the meaning of demographic and descriptive data such as cultural norms and mores, community values, ingrained attitudes, and motives.

Unlike quantitative methods of research, like the survey, which focus on the questions of who, what, where, how much, and how many, and archival analysis, which often situates the participant in some form of historical context, case studies are the preferred strategy when how or why questions are asked. Likewise, they are the preferred method when the researcher has little control over the events, and when there is a contemporary focus within a real life context. In addition, unlike more specifically directed experiments, case studies require a problem that seeks a holistic understanding of the event or situation in question using inductive logic--reasoning from specific to more general terms.

In scholarly circles, case studies are frequently discussed within the context of qualitative research and naturalistic inquiry. Case studies are often referred to interchangeably with ethnography, field study, and participant observation. The underlying philosophical assumptions in the case are similar to these types of qualitative research because each takes place in a natural setting (such as a classroom, neighborhood, or private home), and strives for a more holistic interpretation of the event or situation under study.

Unlike more statistically-based studies which search for quantifiable data, the goal of a case study is to offer new variables and questions for further research. F.H. Giddings, a sociologist in the early part of the century, compares statistical methods to the case study on the basis that the former are concerned with the distribution of a particular trait, or a small number of traits, in a population, whereas the case study is concerned with the whole variety of traits to be found in a particular instance" (Hammersley 95).

Case studies are not a new form of research; naturalistic inquiry was the primary research tool until the development of the scientific method. The fields of sociology and anthropology are credited with the primary shaping of the concept as we know it today. However, case study research has drawn from a number of other areas as well: the clinical methods of doctors; the casework technique being developed by social workers; the methods of historians and anthropologists, plus the qualitative descriptions provided by quantitative researchers like LePlay; and, in the case of Robert Park, the techniques of newspaper reporters and novelists.

Park was an ex-newspaper reporter and editor who became very influential in developing sociological case studies at the University of Chicago in the 1920s. As a newspaper professional he coined the term "scientific" or "depth" reporting: the description of local events in a way that pointed to major social trends. Park viewed the sociologist as "merely a more accurate, responsible, and scientific reporter." Park stressed the variety and value of human experience. He believed that sociology sought to arrive at natural, but fluid, laws and generalizations in regard to human nature and society. These laws weren't static laws of the kind sought by many positivists and natural law theorists, but rather, they were laws of becoming--with a constant possibility of change. Park encouraged students to get out of the library, to quit looking at papers and books, and to view the constant experiment of human experience. He writes, "Go and sit in the lounges of the luxury hotels and on the doorsteps of the flophouses; sit on the Gold Coast settees and on the slum shakedowns; sit in the Orchestra Hall and in the Star and Garter Burlesque. In short, gentlemen [sic], go get the seats of your pants dirty in real research."

But over the years, case studies have drawn their share of criticism. In fact, the method had its detractors from the start. In the 1920s, the debate between pro-qualitative and pro-quantitative became quite heated. Case studies, when compared to statistics, were considered by many to be unscientific. From the 1930's on, the rise of positivism had a growing influence on quantitative methods in sociology. People wanted static, generalizable laws in science. The sociological positivists were looking for stable laws of social phenomena. They criticized case study research because it failed to provide evidence of inter subjective agreement. Also, they condemned it because of the few number of cases studied and that the under-standardized character of their descriptions made generalization impossible. By the 1950s, quantitative methods, in the form of survey research, had become the dominant sociological approach and case study had become a minority practice.

Educational Applications

The 1950's marked the dawning of a new era in case study research, namely that of the utilization of the case study as a teaching method. "Instituted at Harvard Business School in the 1950s as a primary method of teaching, cases have since been used in classrooms and lecture halls alike, either as part of a course of study or as the main focus of the course to which other teaching material is added" (Armisted 1984). The basic purpose of instituting the case method as a teaching strategy was "to transfer much of the responsibility for learning from the teacher on to the student, whose role, as a result, shifts away from passive absorption toward active construction" (Boehrer 1990). Through careful examination and discussion of various cases, "students learn to identify actual problems, to recognize key players and their agendas, and to become aware of those aspects of the situation that contribute to the problem" (Merseth 1991). In addition, students are encouraged to "generate their own analysis of the problems under consideration, to develop their own solutions, and to practically apply their own knowledge of theory to these problems" (Boyce 1993). Along the way, students also develop "the power to analyze and to master a tangled circumstance by identifying and delineating important factors; the ability to utilize ideas, to test them against facts, and to throw them into fresh combinations" (Merseth 1991).

In addition to the practical application and testing of scholarly knowledge, case discussions can also help students prepare for real-world problems, situations and crises by providing an approximation of various professional environments (i.e. classroom, board room, courtroom, or hospital). Thus, through the examination of specific cases, students are given the opportunity to work out their own professional issues through the trials, tribulations, experiences, and research findings of others. An obvious advantage to this mode of instruction is that it allows students the exposure to settings and contexts that they might not otherwise experience. For example, a student interested in studying the effects of poverty on minority secondary student's grade point averages and S.A.T. scores could access and analyze information from schools as geographically diverse as Los Angeles, New York City, Miami, and New Mexico without ever having to leave the classroom.

The case study method also incorporates the idea that students can learn from one another "by engaging with each other and with each other's ideas, by asserting something and then having it questioned, challenged and thrown back at them so that they can reflect on what they hear, and then refine what they say" (Boehrer 1990). In summary, students can direct their own learning by formulating questions and taking responsibility for the study.

Types and Design Concerns

Researchers use multiple methods and approaches to conduct case studies.

Types of Case Studies

Under the more generalized category of case study exist several subdivisions, each of which is custom selected for use depending upon the goals and/or objectives of the investigator. These types of case study include the following:

Illustrative Case Studies These are primarily descriptive studies. They typically utilize one or two instances of an event to show what a situation is like. Illustrative case studies serve primarily to make the unfamiliar familiar and to give readers a common language about the topic in question.

Exploratory (or pilot) Case Studies These are condensed case studies performed before implementing a large scale investigation. Their basic function is to help identify questions and select types of measurement prior to the main investigation. The primary pitfall of this type of study is that initial findings may seem convincing enough to be released prematurely as conclusions.

Cumulative Case Studies These serve to aggregate information from several sites collected at different times. The idea behind these studies is the collection of past studies will allow for greater generalization without additional cost or time being expended on new, possibly repetitive studies.

Critical Instance Case Studies These examine one or more sites for either the purpose of examining a situation of unique interest with little to no interest in generalizability, or to call into question or challenge a highly generalized or universal assertion. This method is useful for answering cause and effect questions.

Identifying a Theoretical Perspective

Much of the case study's design is inherently determined for researchers, depending on the field from which they are working. In composition studies, researchers are typically working from a qualitative, descriptive standpoint. In contrast, physicists will approach their research from a more quantitative perspective. Still, in designing the study, researchers need to make explicit the questions to be explored and the theoretical perspective from which they will approach the case. The three most commonly adopted theories are listed below:

Individual Theories These focus primarily on the individual development, cognitive behavior, personality, learning and disability, and interpersonal interactions of a particular subject.

Organizational Theories These focus on bureaucracies, institutions, organizational structure and functions, or excellence in organizational performance.

Social Theories These focus on urban development, group behavior, cultural institutions, or marketplace functions.

Two examples of case studies are used consistently throughout this chapter. The first, a study produced by Berkenkotter, Huckin, and Ackerman (1988), looks at a first year graduate student's initiation into an academic writing program. The study uses participant-observer and linguistic data collecting techniques to assess the student's knowledge of appropriate discourse conventions. Using the pseudonym Nate to refer to the subject, the study sought to illuminate the particular experience rather than to generalize about the experience of fledgling academic writers collectively.

For example, in Berkenkotter, Huckin, and Ackerman's (1988) study we are told that the researchers are interested in disciplinary communities. In the first paragraph, they ask what constitutes membership in a disciplinary community and how achieving membership might affect a writer's understanding and production of texts. In the third paragraph they state that researchers must negotiate their claims "within the context of his sub specialty's accepted knowledge and methodology." In the next paragraph they ask, "How is literacy acquired? What is the process through which novices gain community membership? And what factors either aid or hinder students learning the requisite linguistic behaviors?" This introductory section ends with a paragraph in which the study's authors claim that during the course of the study, the subject, Nate, successfully makes the transition from "skilled novice" to become an initiated member of the academic discourse community and that his texts exhibit linguistic changes which indicate this transition. In the next section the authors make explicit the sociolinguistic theoretical and methodological assumptions on which the study is based (1988). Thus the reader has a good understanding of the authors' theoretical background and purpose in conducting the study even before it is explicitly stated on the fourth page of the study. "Our purpose was to examine the effects of the educational context on one graduate student's production of texts as he wrote in different courses and for different faculty members over the academic year 1984-85." The goal of the study then, was to explore the idea that writers must be initiated into a writing community, and that this initiation will change the way one writes.

The second example is Janet Emig's (1971) study of the composing process of a group of twelfth graders. In this study, Emig seeks to answer the question of what happens to the self as a result educational stimuli in terms of academic writing. The case study used methods such as protocol analysis, tape-recorded interviews, and discourse analysis.

In the case of Janet Emig's (1971) study of the composing process of eight twelfth graders, four specific hypotheses were made:

• Twelfth grade writers engage in two modes of composing: reflexive and extensive.
• These differences can be ascertained and characterized through having the writers compose aloud their composition process.
• A set of implied stylistic principles governs the writing process.
• For twelfth grade writers, extensive writing occurs chiefly as a school-sponsored activity, or reflexive, as a self-sponsored activity.

In this study, the chief distinction is between the two dominant modes of composing among older, secondary school students. The distinctions are:

• The reflexive mode, which focuses on the writer's thoughts and feelings.
• The extensive mode, which focuses on conveying a message.

Emig also outlines the specific questions which guided the research in the opening pages of her Review of Literature , preceding the report.

Designing a Case Study

After considering the different sub categories of case study and identifying a theoretical perspective, researchers can begin to design their study. Research design is the string of logic that ultimately links the data to be collected and the conclusions to be drawn to the initial questions of the study. Typically, research designs deal with at least four problems:

• What questions to study
• What data are relevant
• What data to collect
• How to analyze that data

In other words, a research design is basically a blueprint for getting from the beginning to the end of a study. The beginning is an initial set of questions to be answered, and the end is some set of conclusions about those questions.

Because case studies are conducted on topics as diverse as Anglo-Saxon Literature (Thrane 1986) and AIDS prevention (Van Vugt 1994), it is virtually impossible to outline any strict or universal method or design for conducting the case study. However, Robert K. Yin (1993) does offer five basic components of a research design:

• A study's questions.
• A study's propositions (if any).
• A study's units of analysis.
• The logic that links the data to the propositions.
• The criteria for interpreting the findings.

In addition to these five basic components, Yin also stresses the importance of clearly articulating one's theoretical perspective, determining the goals of the study, selecting one's subject(s), selecting the appropriate method(s) of collecting data, and providing some considerations to the composition of the final report.

Conducting Case Studies

To obtain as complete a picture of the participant as possible, case study researchers can employ a variety of approaches and methods. These approaches, methods, and related issues are discussed in depth in this section.

Method: Single or Multi-modal?

To obtain as complete a picture of the participant as possible, case study researchers can employ a variety of methods. Some common methods include interviews , protocol analyses, field studies, and participant-observations. Emig (1971) chose to use several methods of data collection. Her sources included conversations with the students, protocol analysis, discrete observations of actual composition, writing samples from each student, and school records (Lauer and Asher 1988).

Berkenkotter, Huckin, and Ackerman (1988) collected data by observing classrooms, conducting faculty and student interviews, collecting self reports from the subject, and by looking at the subject's written work.

A study that was criticized for using a single method model was done by Flower and Hayes (1984). In this study that explores the ways in which writers use different forms of knowing to create space, the authors used only protocol analysis to gather data. The study came under heavy fire because of their decision to use only one method.

Participant Selection

Case studies can use one participant, or a small group of participants. However, it is important that the participant pool remain relatively small. The participants can represent a diverse cross section of society, but this isn't necessary.

For example, the Berkenkotter, Huckin, and Ackerman (1988) study looked at just one participant, Nate. By contrast, in Janet Emig's (1971) study of the composition process of twelfth graders, eight participants were selected representing a diverse cross section of the community, with volunteers from an all-white upper-middle-class suburban school, an all-black inner-city school, a racially mixed lower-middle-class school, an economically and racially mixed school, and a university school.

Often, a brief "case history" is done on the participants of the study in order to provide researchers with a clearer understanding of their participants, as well as some insight as to how their own personal histories might affect the outcome of the study. For instance, in Emig's study, the investigator had access to the school records of five of the participants, and to standardized test scores for the remaining three. Also made available to the researcher was the information that three of the eight students were selected as NCTE Achievement Award winners. These personal histories can be useful in later stages of the study when data are being analyzed and conclusions drawn.

Data Collection

There are six types of data collected in case studies:

• Archival records.
• Interviews.
• Direct observation.
• Participant observation.

In the field of composition research, these six sources might be:

• A writer's drafts.
• School records of student writers.
• Transcripts of interviews with a writer.
• Transcripts of conversations between writers (and protocols).
• Videotapes and notes from direct field observations.
• Hard copies of a writer's work on computer.

Depending on whether researchers have chosen to use a single or multi-modal approach for the case study, they may choose to collect data from one or any combination of these sources.

Protocols, that is, transcriptions of participants talking aloud about what they are doing as they do it, have been particularly common in composition case studies. For example, in Emig's (1971) study, the students were asked, in four different sessions, to give oral autobiographies of their writing experiences and to compose aloud three themes in the presence of a tape recorder and the investigator.

In some studies, only one method of data collection is conducted. For example, the Flower and Hayes (1981) report on the cognitive process theory of writing depends on protocol analysis alone. However, using multiple sources of evidence to increase the reliability and validity of the data can be advantageous.

Case studies are likely to be much more convincing and accurate if they are based on several different sources of information, following a corroborating mode. This conclusion is echoed among many composition researchers. For example, in her study of predrafting processes of high and low-apprehensive writers, Cynthia Selfe (1985) argues that because "methods of indirect observation provide only an incomplete reflection of the complex set of processes involved in composing, a combination of several such methods should be used to gather data in any one study." Thus, in this study, Selfe collected her data from protocols, observations of students role playing their writing processes, audio taped interviews with the students, and videotaped observations of the students in the process of composing.

It can be said then, that cross checking data from multiple sources can help provide a multidimensional profile of composing activities in a particular setting. Sharan Merriam (1985) suggests "checking, verifying, testing, probing, and confirming collected data as you go, arguing that this process will follow in a funnel-like design resulting in less data gathering in later phases of the study along with a congruent increase in analysis checking, verifying, and confirming."

It is important to note that in case studies, as in any qualitative descriptive research, while researchers begin their studies with one or several questions driving the inquiry (which influence the key factors the researcher will be looking for during data collection), a researcher may find new key factors emerging during data collection. These might be unexpected patterns or linguistic features which become evident only during the course of the research. While not bearing directly on the researcher's guiding questions, these variables may become the basis for new questions asked at the end of the report, thus linking to the possibility of further research.

Data Analysis

As the information is collected, researchers strive to make sense of their data. Generally, researchers interpret their data in one of two ways: holistically or through coding. Holistic analysis does not attempt to break the evidence into parts, but rather to draw conclusions based on the text as a whole. Flower and Hayes (1981), for example, make inferences from entire sections of their students' protocols, rather than searching through the transcripts to look for isolatable characteristics.

However, composition researchers commonly interpret their data by coding, that is by systematically searching data to identify and/or categorize specific observable actions or characteristics. These observable actions then become the key variables in the study. Sharan Merriam (1988) suggests seven analytic frameworks for the organization and presentation of data:

• The role of participants.
• The network analysis of formal and informal exchanges among groups.
• Historical.
• Thematical.
• Ritual and symbolism.
• Critical incidents that challenge or reinforce fundamental beliefs, practices, and values.

There are two purposes of these frameworks: to look for patterns among the data and to look for patterns that give meaning to the case study.

As stated above, while most researchers begin their case studies expecting to look for particular observable characteristics, it is not unusual for key variables to emerge during data collection. Typical variables coded in case studies of writers include pauses writers make in the production of a text, the use of specific linguistic units (such as nouns or verbs), and writing processes (planning, drafting, revising, and editing). In the Berkenkotter, Huckin, and Ackerman (1988) study, for example, researchers coded the participant's texts for use of connectives, discourse demonstratives, average sentence length, off-register words, use of the first person pronoun, and the ratio of definite articles to indefinite articles.

Since coding is inherently subjective, more than one coder is usually employed. In the Berkenkotter, Huckin, and Ackerman (1988) study, for example, three rhetoricians were employed to code the participant's texts for off-register phrases. The researchers established the agreement among the coders before concluding that the participant used fewer off-register words as the graduate program progressed.

Composing the Case Study Report

In the many forms it can take, "a case study is generically a story; it presents the concrete narrative detail of actual, or at least realistic events, it has a plot, exposition, characters, and sometimes even dialogue" (Boehrer 1990). Generally, case study reports are extensively descriptive, with "the most problematic issue often referred to as being the determination of the right combination of description and analysis" (1990). Typically, authors address each step of the research process, and attempt to give the reader as much context as possible for the decisions made in the research design and for the conclusions drawn.

This contextualization usually includes a detailed explanation of the researchers' theoretical positions, of how those theories drove the inquiry or led to the guiding research questions, of the participants' backgrounds, of the processes of data collection, of the training and limitations of the coders, along with a strong attempt to make connections between the data and the conclusions evident.

Although the Berkenkotter, Huckin, and Ackerman (1988) study does not, case study reports often include the reactions of the participants to the study or to the researchers' conclusions. Because case studies tend to be exploratory, most end with implications for further study. Here researchers may identify significant variables that emerged during the research and suggest studies related to these, or the authors may suggest further general questions that their case study generated.

For example, Emig's (1971) study concludes with a section dedicated solely to the topic of implications for further research, in which she suggests several means by which this particular study could have been improved, as well as questions and ideas raised by this study which other researchers might like to address, such as: is there a correlation between a certain personality and a certain composing process profile (e.g. is there a positive correlation between ego strength and persistence in revising)?

Also included in Emig's study is a section dedicated to implications for teaching, which outlines the pedagogical ramifications of the study's findings for teachers currently involved in high school writing programs.

Sharan Merriam (1985) also offers several suggestions for alternative presentations of data:

• Prepare specialized condensations for appropriate groups.
• Replace narrative sections with a series of answers to open-ended questions.
• Present "skimmer's" summaries at beginning of each section.
• Incorporate headlines that encapsulate information from text.
• Prepare analytic summaries with supporting data appendixes.
• Present data in colorful and/or unique graphic representations.

Issues of Validity and Reliability

Once key variables have been identified, they can be analyzed. Reliability becomes a key concern at this stage, and many case study researchers go to great lengths to ensure that their interpretations of the data will be both reliable and valid. Because issues of validity and reliability are an important part of any study in the social sciences, it is important to identify some ways of dealing with results.

Multi-modal case study researchers often balance the results of their coding with data from interviews or writer's reflections upon their own work. Consequently, the researchers' conclusions become highly contextualized. For example, in a case study which looked at the time spent in different stages of the writing process, Berkenkotter concluded that her participant, Donald Murray, spent more time planning his essays than in other writing stages. The report of this case study is followed by Murray's reply, wherein he agrees with some of Berkenkotter's conclusions and disagrees with others.

As is the case with other research methodologies, issues of external validity, construct validity, and reliability need to be carefully considered.

Commentary on Case Studies

Researchers often debate the relative merits of particular methods, among them case study. In this section, we comment on two key issues. To read the commentaries, choose any of the items below:

Strengths and Weaknesses of Case Studies

Most case study advocates point out that case studies produce much more detailed information than what is available through a statistical analysis. Advocates will also hold that while statistical methods might be able to deal with situations where behavior is homogeneous and routine, case studies are needed to deal with creativity, innovation, and context. Detractors argue that case studies are difficult to generalize because of inherent subjectivity and because they are based on qualitative subjective data, generalizable only to a particular context.

Flexibility

The case study approach is a comparatively flexible method of scientific research. Because its project designs seem to emphasize exploration rather than prescription or prediction, researchers are comparatively freer to discover and address issues as they arise in their experiments. In addition, the looser format of case studies allows researchers to begin with broad questions and narrow their focus as their experiment progresses rather than attempt to predict every possible outcome before the experiment is conducted.

Emphasis on Context

By seeking to understand as much as possible about a single subject or small group of subjects, case studies specialize in "deep data," or "thick description"--information based on particular contexts that can give research results a more human face. This emphasis can help bridge the gap between abstract research and concrete practice by allowing researchers to compare their firsthand observations with the quantitative results obtained through other methods of research.

Inherent Subjectivity

"The case study has long been stereotyped as the weak sibling among social science methods," and is often criticized as being too subjective and even pseudo-scientific. Likewise, "investigators who do case studies are often regarded as having deviated from their academic disciplines, and their investigations as having insufficient precision (that is, quantification), objectivity and rigor" (Yin 1989). Opponents cite opportunities for subjectivity in the implementation, presentation, and evaluation of case study research. The approach relies on personal interpretation of data and inferences. Results may not be generalizable, are difficult to test for validity, and rarely offer a problem-solving prescription. Simply put, relying on one or a few subjects as a basis for cognitive extrapolations runs the risk of inferring too much from what might be circumstance.

High Investment

Case studies can involve learning more about the subjects being tested than most researchers would care to know--their educational background, emotional background, perceptions of themselves and their surroundings, their likes, dislikes, and so on. Because of its emphasis on "deep data," the case study is out of reach for many large-scale research projects which look at a subject pool in the tens of thousands. A budget request of $10,000 to examine 200 subjects sounds more efficient than a similar request to examine four subjects.

Ethical Considerations

Researchers conducting case studies should consider certain ethical issues. For example, many educational case studies are often financed by people who have, either directly or indirectly, power over both those being studied and those conducting the investigation (1985). This conflict of interests can hinder the credibility of the study.

The personal integrity, sensitivity, and possible prejudices and/or biases of the investigators need to be taken into consideration as well. Personal biases can creep into how the research is conducted, alternative research methods used, and the preparation of surveys and questionnaires.

A common complaint in case study research is that investigators change direction during the course of the study unaware that their original research design was inadequate for the revised investigation. Thus, the researchers leave unknown gaps and biases in the study. To avoid this, researchers should report preliminary findings so that the likelihood of bias will be reduced.

Concerns about Reliability, Validity, and Generalizability

Merriam (1985) offers several suggestions for how case study researchers might actively combat the popular attacks on the validity, reliability, and generalizability of case studies:

• Prolong the Processes of Data Gathering on Site: This will help to insure the accuracy of the findings by providing the researcher with more concrete information upon which to formulate interpretations.
• Employ the Process of "Triangulation": Use a variety of data sources as opposed to relying solely upon one avenue of observation. One example of such a data check would be what McClintock, Brannon, and Maynard (1985) refer to as a "case cluster method," that is, when a single unit within a larger case is randomly sampled, and that data treated quantitatively." For instance, in Emig's (1971) study, the case cluster method was employed, singling out the productivity of a single student named Lynn. This cluster profile included an advanced case history of the subject, specific examination and analysis of individual compositions and protocols, and extensive interview sessions. The seven remaining students were then compared with the case of Lynn, to ascertain if there are any shared, or unique dimensions to the composing process engaged in by these eight students.
• Conduct Member Checks: Initiate and maintain an active corroboration on the interpretation of data between the researcher and those who provided the data. In other words, talk to your subjects.
• Collect Referential Materials: Complement the file of materials from the actual site with additional document support. For example, Emig (1971) supports her initial propositions with historical accounts by writers such as T.S. Eliot, James Joyce, and D.H. Lawrence. Emig also cites examples of theoretical research done with regards to the creative process, as well as examples of empirical research dealing with the writing of adolescents. Specific attention is then given to the four stages description of the composing process delineated by Helmoltz, Wallas, and Cowley, as it serves as the focal point in this study.
• Engage in Peer Consultation: Prior to composing the final draft of the report, researchers should consult with colleagues in order to establish validity through pooled judgment.

Although little can be done to combat challenges concerning the generalizability of case studies, "most writers suggest that qualitative research should be judged as credible and confirmable as opposed to valid and reliable" (Merriam 1985). Likewise, it has been argued that "rather than transplanting statistical, quantitative notions of generalizability and thus finding qualitative research inadequate, it makes more sense to develop an understanding of generalization that is congruent with the basic characteristics of qualitative inquiry" (1985). After all, criticizing the case study method for being ungeneralizable is comparable to criticizing a washing machine for not being able to tell the correct time. In other words, it is unjust to criticize a method for not being able to do something which it was never originally designed to do in the first place.

Annotated Bibliography

Armisted, C. (1984). How Useful are Case Studies. Training and Development Journal, 38 (2), 75-77.

This article looks at eight types of case studies, offers pros and cons of using case studies in the classroom, and gives suggestions for successfully writing and using case studies.

Bardovi-Harlig, K. (1997). Beyond Methods: Components of Second Language Teacher Education . New York: McGraw-Hill.

A compilation of various research essays which address issues of language teacher education. Essays included are: "Non-native reading research and theory" by Lee, "The case for Psycholinguistics" by VanPatten, and "Assessment and Second Language Teaching" by Gradman and Reed.

Bartlett, L. (1989). A Question of Good Judgment; Interpretation Theory and Qualitative Enquiry Address. 70th Annual Meeting of the American Educational Research Association. San Francisco.

Bartlett selected "quasi-historical" methodology, which focuses on the "truth" found in case records, as one that will provide "good judgments" in educational inquiry. He argues that although the method is not comprehensive, it can try to connect theory with practice.

Baydere, S. et. al. (1993). Multimedia conferencing as a tool for collaborative writing: a case study in Computer Supported Collaborative Writing. New York: Springer-Verlag.

The case study by Baydere et. al. is just one of the many essays in this book found in the series "Computer Supported Cooperative Work." Denley, Witefield and May explore similar issues in their essay, "A case study in task analysis for the design of a collaborative document production system."

Berkenkotter, C., Huckin, T., N., & Ackerman J. (1988). Conventions, Conversations, and the Writer: Case Study of a Student in a Rhetoric Ph.D. Program. Research in the Teaching of English, 22, 9-44.

The authors focused on how the writing of their subject, Nate or Ackerman, changed as he became more acquainted or familiar with his field's discourse community.

Berninger, V., W., and Gans, B., M. (1986). Language Profiles in Nonspeaking Individuals of Normal Intelligence with Severe Cerebral Palsy. Augmentative and Alternative Communication, 2, 45-50.

Argues that generalizations about language abilities in patients with severe cerebral palsy (CP) should be avoided. Standardized tests of different levels of processing oral language, of processing written language, and of producing written language were administered to 3 male participants (aged 9, 16, and 40 yrs).

Bockman, J., R., and Couture, B. (1984). The Case Method in Technical Communication: Theory and Models. Texas: Association of Teachers of Technical Writing.

Examines the study and teaching of technical writing, communication of technical information, and the case method in terms of those applications.

Boehrer, J. (1990). Teaching With Cases: Learning to Question. New Directions for Teaching and Learning, 42 41-57.

This article discusses the origins of the case method, looks at the question of what is a case, gives ideas about learning in case teaching, the purposes it can serve in the classroom, the ground rules for the case discussion, including the role of the question, and new directions for case teaching.

Bowman, W. R. (1993). Evaluating JTPA Programs for Economically Disadvantaged Adults: A Case Study of Utah and General Findings . Washington: National Commission for Employment Policy.

"To encourage state-level evaluations of JTPA, the Commission and the State of Utah co-sponsored this report on the effectiveness of JTPA Title II programs for adults in Utah. The technique used is non-experimental and the comparison group was selected from registrants with Utah's Employment Security. In a step-by-step approach, the report documents how non-experimental techniques can be applied and several specific technical issues can be addressed."

Boyce, A. (1993) The Case Study Approach for Pedagogists. Annual Meeting of the American Alliance for Health, Physical Education, Recreation and Dance. (Address). Washington DC.

This paper addresses how case studies 1) bridge the gap between teaching theory and application, 2) enable students to analyze problems and develop solutions for situations that will be encountered in the real world of teaching, and 3) helps students to evaluate the feasibility of alternatives and to understand the ramifications of a particular course of action.

Carson, J. (1993) The Case Study: Ideal Home of WAC Quantitative and Qualitative Data. Annual Meeting of the Conference on College Composition and Communication. (Address). San Diego.

"Increasingly, one of the most pressing questions for WAC advocates is how to keep [WAC] programs going in the face of numerous difficulties. Case histories offer the best chance for fashioning rhetorical arguments to keep WAC programs going because they offer the opportunity to provide a coherent narrative that contextualizes all documents and data, including what is generally considered scientific data. A case study of the WAC program, . . . at Robert Morris College in Pittsburgh demonstrates the advantages of this research method. Such studies are ideal homes for both naturalistic and positivistic data as well as both quantitative and qualitative information."

---. (1991). A Cognitive Process Theory of Writing. College Composition and Communication. 32. 365-87.

No abstract available.

Cromer, R. (1994) A Case Study of Dissociations Between Language and Cognition. Constraints on Language Acquisition: Studies of Atypical Children . Hillsdale: Lawrence Erlbaum Associates, 141-153.

Crossley, M. (1983) Case Study in Comparative and International Education: An Approach to Bridging the Theory-Practice Gap. Proceedings of the 11th Annual Conference of the Australian Comparative and International Education Society. Hamilton, NZ.

Case study research, as presented here, helps bridge the theory-practice gap in comparative and international research studies of education because it focuses on the practical, day-to-day context rather than on the national arena. The paper asserts that the case study method can be valuable at all levels of research, formation, and verification of theories in education.

Daillak, R., H., and Alkin, M., C. (1982). Qualitative Studies in Context: Reflections on the CSE Studies of Evaluation Use . California: EDRS

The report shows how the Center of the Study of Evaluation (CSE) applied qualitative techniques to a study of evaluation information use in local, Los Angeles schools. It critiques the effectiveness and the limitations of using case study, evaluation, field study, and user interview survey methodologies.

Davey, L. (1991). The Application of Case Study Evaluations. ERIC/TM Digest.

This article examines six types of case studies, the type of evaluation questions that can be answered, the functions served, some design features, and some pitfalls of the method.

Deutch, C. E. (1996). A course in research ethics for graduate students. College Teaching, 44, 2, 56-60.

This article describes a one-credit discussion course in research ethics for graduate students in biology. Case studies are focused on within the four parts of the course: 1) major issues, 2 )practical issues in scholarly work, 3) ownership of research results, and 4) training and personal decisions.

DeVoss, G. (1981). Ethics in Fieldwork Research. RIE 27p. (ERIC)

This article examines four of the ethical problems that can happen when conducting case study research: acquiring permission to do research, knowing when to stop digging, the pitfalls of doing collaborative research, and preserving the integrity of the participants.

Driscoll, A. (1985). Case Study of a Research Intervention: the University of Utah’s Collaborative Approach . San Francisco: Far West Library for Educational Research Development.

Paper presented at the annual meeting of the American Association of Colleges of Teacher Education, Denver, CO, March 1985. Offers information of in-service training, specifically case studies application.

Ellram, L. M. (1996). The Use of the Case Study Method in Logistics Research. Journal of Business Logistics, 17, 2, 93.

This article discusses the increased use of case study in business research, and the lack of understanding of when and how to use case study methodology in business.

Emig, J. (1971) The Composing Processes of Twelfth Graders . Urbana: NTCE.

This case study uses observation, tape recordings, writing samples, and school records to show that writing in reflexive and extensive situations caused different lengths of discourse and different clusterings of the components of the writing process.

Feagin, J. R. (1991). A Case For the Case Study . Chapel Hill: The University of North Carolina Press.

This book discusses the nature, characteristics, and basic methodological issues of the case study as a research method.

Feldman, H., Holland, A., & Keefe, K. (1989) Language Abilities after Left Hemisphere Brain Injury: A Case Study of Twins. Topics in Early Childhood Special Education, 9, 32-47.

"Describes the language abilities of 2 twin pairs in which 1 twin (the experimental) suffered brain injury to the left cerebral hemisphere around the time of birth and1 twin (the control) did not. One pair of twins was initially assessed at age 23 mo. and the other at about 30 mo.; they were subsequently evaluated in their homes 3 times at about 6-mo intervals."

Fidel, R. (1984). The Case Study Method: A Case Study. Library and Information Science Research, 6.

The article describes the use of case study methodology to systematically develop a model of online searching behavior in which study design is flexible, subject manner determines data gathering and analyses, and procedures adapt to the study's progressive change.

Flower, L., & Hayes, J. R. (1984). Images, Plans and Prose: The Representation of Meaning in Writing. Written Communication, 1, 120-160.

Explores the ways in which writers actually use different forms of knowing to create prose.

Frey, L. R. (1992). Interpreting Communication Research: A Case Study Approach Englewood Cliffs, N.J.: Prentice Hall.

The book discusses research methodologies in the Communication field. It focuses on how case studies bridge the gap between communication research, theory, and practice.

Gilbert, V. K. (1981). The Case Study as a Research Methodology: Difficulties and Advantages of Integrating the Positivistic, Phenomenological and Grounded Theory Approaches . The Annual Meeting of the Canadian Association for the Study of Educational Administration. (Address) Halifax, NS, Can.

This study on an innovative secondary school in England shows how a "low-profile" participant-observer case study was crucial to the initial observation, the testing of hypotheses, the interpretive approach, and the grounded theory.

Gilgun, J. F. (1994). A Case for Case Studies in Social Work Research. Social Work, 39, 4, 371-381.

This article defines case study research, presents guidelines for evaluation of case studies, and shows the relevance of case studies to social work research. It also looks at issues such as evaluation and interpretations of case studies.

Glennan, S. L., Sharp-Bittner, M. A. & Tullos, D. C. (1991). Augmentative and Alternative Communication Training with a Nonspeaking Adult: Lessons from MH. Augmentative and Alternative Communication, 7, 240-7.

"A response-guided case study documented changes in a nonspeaking 36-yr-old man's ability to communicate using 3 trained augmentative communication modes. . . . Data were collected in videotaped interaction sessions between the nonspeaking adult and a series of adult speaking."

Graves, D. (1981). An Examination of the Writing Processes of Seven Year Old Children. Research in the Teaching of English, 15, 113-134.

Hamel, J. (1993). Case Study Methods . Newbury Park: Sage. .

"In a most economical fashion, Hamel provides a practical guide for producing theoretically sharp and empirically sound sociological case studies. A central idea put forth by Hamel is that case studies must "locate the global in the local" thus making the careful selection of the research site the most critical decision in the analytic process."

Karthigesu, R. (1986, July). Television as a Tool for Nation-Building in the Third World: A Post-Colonial Pattern, Using Malaysia as a Case-Study. International Television Studies Conference. (Address). London, 10-12.

"The extent to which Television Malaysia, as a national mass media organization, has been able to play a role in nation building in the post-colonial period is . . . studied in two parts: how the choice of a model of nation building determines the character of the organization; and how the character of the organization influences the output of the organization."

Kenny, R. (1984). Making the Case for the Case Study. Journal of Curriculum Studies, 16, (1), 37-51.

The article looks at how and why the case study is justified as a viable and valuable approach to educational research and program evaluation.

Knirk, F. (1991). Case Materials: Research and Practice. Performance Improvement Quarterly, 4 (1 ), 73-81.

The article addresses the effectiveness of case studies, subject areas where case studies are commonly used, recent examples of their use, and case study design considerations.

Klos, D. (1976). Students as Case Writers. Teaching of Psychology, 3.2, 63-66.

This article reviews a course in which students gather data for an original case study of another person. The task requires the students to design the study, collect the data, write the narrative, and interpret the findings.

Leftwich, A. (1981). The Politics of Case Study: Problems of Innovation in University Education. Higher Education Review, 13.2, 38-64.

The article discusses the use of case studies as a teaching method. Emphasis is on the instructional materials, interdisciplinarity, and the complex relationships within the university that help or hinder the method.

Mabrito, M. (1991, Oct.). Electronic Mail as a Vehicle for Peer Response: Conversations of High and Low Apprehensive Writers. Written Communication, 509-32.

McCarthy, S., J. (1955). The Influence of Classroom Discourse on Student Texts: The Case of Ella . East Lansing: Institute for Research on Teaching.

A look at how students of color become marginalized within traditional classroom discourse. The essay follows the struggles of one black student: Ella.

Matsuhashi, A., ed. (1987). Writing in Real Time: Modeling Production Processes Norwood, NJ: Ablex Publishing Corporation.

Investigates how writers plan to produce discourse for different purposes to report, to generalize, and to persuade, as well as how writers plan for sentence level units of language. To learn about planning, an observational measure of pause time was used" (ERIC).

Merriam, S. B. (1985). The Case Study in Educational Research: A Review of Selected Literature. Journal of Educational Thought, 19.3, 204-17.

The article examines the characteristics of, philosophical assumptions underlying the case study, the mechanics of conducting a case study, and the concerns about the reliability, validity, and generalizability of the method.

---. (1988). Case Study Research in Education: A Qualitative Approach San Francisco: Jossey Bass.

Merry, S. E., & Milner, N. eds. (1993). The Possibility of Popular Justice: A Case Study of Community Mediation in the United States . Ann Arbor: U of Michigan.

". . . this volume presents a case study of one experiment in popular justice, the San Francisco Community Boards. This program has made an explicit claim to create an alternative justice, or new justice, in the midst of a society ordered by state law. The contributors to this volume explore the history and experience of the program and compare it to other versions of popular justice in the United States, Europe, and the Third World."

Merseth, K. K. (1991). The Case for Cases in Teacher Education. RIE. 42p. (ERIC).

This monograph argues that the case method of instruction offers unique potential for revitalizing the field of teacher education.

Michaels, S. (1987). Text and Context: A New Approach to the Study of Classroom Writing. Discourse Processes, 10, 321-346.

"This paper argues for and illustrates an approach to the study of writing that integrates ethnographic analysis of classroom interaction with linguistic analysis of written texts and teacher/student conversational exchanges. The approach is illustrated through a case study of writing in a single sixth grade classroom during a single writing assignment."

Milburn, G. (1995). Deciphering a Code or Unraveling a Riddle: A Case Study in the Application of a Humanistic Metaphor to the Reporting of Social Studies Teaching. Theory and Research in Education, 13.

This citation serves as an example of how case studies document learning procedures in a senior-level economics course.

Milley, J. E. (1979). An Investigation of Case Study as an Approach to Program Evaluation. 19th Annual Forum of the Association for Institutional Research. (Address). San Diego.

The case study method merged a narrative report focusing on the evaluator as participant-observer with document review, interview, content analysis, attitude questionnaire survey, and sociogram analysis. Milley argues that case study program evaluation has great potential for widespread use.

Minnis, J. R. (1985, Sept.). Ethnography, Case Study, Grounded Theory, and Distance Education Research. Distance Education, 6.2.

This article describes and defines the strengths and weaknesses of ethnography, case study, and grounded theory.

Nunan, D. (1992). Collaborative language learning and teaching . New York: Cambridge University Press.

Included in this series of essays is Peter Sturman’s "Team Teaching: a case study from Japan" and David Nunan’s own "Toward a collaborative approach to curriculum development: a case study."

Nystrand, M., ed. (1982). What Writers Know: The Language, Process, and Structure of Written Discourse . New York: Academic Press.

Owenby, P. H. (1992). Making Case Studies Come Alive. Training, 29, (1), 43-46. (ERIC)

This article provides tips for writing more effective case studies.

---. (1981). Pausing and Planning: The Tempo of Writer Discourse Production. Research in the Teaching of English, 15 (2),113-34.

Perl, S. (1979). The Composing Processes of Unskilled College Writers. Research in the Teaching of English, 13, 317-336.

"Summarizes a study of five unskilled college writers, focusing especially on one of the five, and discusses the findings in light of current pedagogical practice and research design."

Pilcher J. and A. Coffey. eds. (1996). Gender and Qualitative Research . Brookfield: Aldershot, Hants, England.

This book provides a series of essays which look at gender identity research, qualitative research and applications of case study to questions of gendered pedagogy.

Pirie, B. S. (1993). The Case of Morty: A Four Year Study. Gifted Education International, 9 (2), 105-109.

This case study describes a boy from kindergarten through third grade with above average intelligence but difficulty in learning to read, write, and spell.

Popkewitz, T. (1993). Changing Patterns of Power: Social Regulation and Teacher Education Reform. Albany: SUNY Press.

Popkewitz edits this series of essays that address case studies on educational change and the training of teachers. The essays vary in terms of discipline and scope. Also, several authors include case studies of educational practices in countries other than the United States.

---. (1984). The Predrafting Processes of Four High- and Four Low Apprehensive Writers. Research in the Teaching of English, 18, (1), 45-64.

Rasmussen, P. (1985, March) A Case Study on the Evaluation of Research at the Technical University of Denmark. International Journal of Institutional Management in Higher Education, 9 (1).

This is an example of a case study methodology used to evaluate the chemistry and chemical engineering departments at the University of Denmark.

Roth, K. J. (1986). Curriculum Materials, Teacher Talk, and Student Learning: Case Studies in Fifth-Grade Science Teaching . East Lansing: Institute for Research on Teaching.

Roth offers case studies on elementary teachers, elementary school teaching, science studies and teaching, and verbal learning.

Selfe, C. L. (1985). An Apprehensive Writer Composes. When a Writer Can't Write: Studies in Writer's Block and Other Composing-Process Problems . (pp. 83-95). Ed. Mike Rose. NMY: Guilford.

Smith-Lewis, M., R. and Ford, A. (1987). A User's Perspective on Augmentative Communication. Augmentative and Alternative Communication, 3, 12-7.

"During a series of in-depth interviews, a 25-yr-old woman with cerebral palsy who utilized augmentative communication reflected on the effectiveness of the devices designed for her during her school career."

St. Pierre, R., G. (1980, April). Follow Through: A Case Study in Metaevaluation Research . 64th Annual Meeting of the American Educational Research Association. (Address).

The three approaches to metaevaluation are evaluation of primary evaluations, integrative meta-analysis with combined primary evaluation results, and re-analysis of the raw data from a primary evaluation.

Stahler, T., M. (1996, Feb.) Early Field Experiences: A Model That Worked. ERIC.

"This case study of a field and theory class examines a model designed to provide meaningful field experiences for preservice teachers while remaining consistent with the instructor's beliefs about the role of teacher education in preparing teachers for the classroom."

Stake, R. E. (1995). The Art of Case Study Research. Thousand Oaks: Sage Publications.

This book examines case study research in education and case study methodology.

Stiegelbauer, S. (1984) Community, Context, and Co-curriculum: Situational Factors Influencing School Improvements in a Study of High Schools. Presented at the annual meeting of the American Educational Research Association, New Orleans, LA.

Discussion of several case studies: one looking at high school environments, another examining educational innovations.

Stolovitch, H. (1990). Case Study Method. Performance And Instruction, 29, (9), 35-37.

This article describes the case study method as a form of simulation and presents guidelines for their use in professional training situations.

Thaller, E. (1994). Bibliography for the Case Method: Using Case Studies in Teacher Education. RIE. 37 p.

This bibliography presents approximately 450 citations on the use of case studies in teacher education from 1921-1993.

Thrane, T. (1986). On Delimiting the Senses of Near-Synonyms in Historical Semantics: A Case Study of Adjectives of 'Moral Sufficiency' in the Old English Andreas. Linguistics Across Historical and Geographical Boundaries: In Honor of Jacek Fisiak on the Occasion of his Fiftieth Birthday . Berlin: Mouton de Gruyter.

United Nations. (1975). Food and Agriculture Organization. Report on the FAO/UNFPA Seminar on Methodology, Research and Country: Case Studies on Population, Employment and Productivity . Rome: United Nations.

This example case study shows how the methodology can be used in a demographic and psychographic evaluation. At the same time, it discusses the formation and instigation of the case study methodology itself.

Van Vugt, J. P., ed. (1994). Aids Prevention and Services: Community Based Research . Westport: Bergin and Garvey.

"This volume has been five years in the making. In the process, some of the policy applications called for have met with limited success, such as free needle exchange programs in a limited number of American cities, providing condoms to prison inmates, and advertisements that depict same-sex couples. Rather than dating our chapters that deal with such subjects, such policy applications are verifications of the type of research demonstrated here. Furthermore, they indicate the critical need to continue community based research in the various communities threatened by acquired immuno-deficiency syndrome (AIDS) . . . "

Welch, W., ed. (1981, May). Case Study Methodology in Educational Evaluation. Proceedings of the Minnesota Evaluation Conference. Minnesota. (Address).

The four papers in these proceedings provide a comprehensive picture of the rationale, methodology, strengths, and limitations of case studies.

Williams, G. (1987). The Case Method: An Approach to Teaching and Learning in Educational Administration. RIE, 31p.

This paper examines the viability of the case method as a teaching and learning strategy in instructional systems geared toward the training of personnel of the administration of various aspects of educational systems.

Yin, R. K. (1993). Advancing Rigorous Methodologies: A Review of 'Towards Rigor in Reviews of Multivocal Literatures.' Review of Educational Research, 61, (3).

"R. T. Ogawa and B. Malen's article does not meet its own recommended standards for rigorous testing and presentation of its own conclusions. Use of the exploratory case study to analyze multivocal literatures is not supported, and the claim of grounded theory to analyze multivocal literatures may be stronger."

---. (1989). Case Study Research: Design and Methods. London: Sage Publications Inc.

This book discusses in great detail, the entire design process of the case study, including entire chapters on collecting evidence, analyzing evidence, composing the case study report, and designing single and multiple case studies.

Related Links

Consider the following list of related Web sites for more information on the topic of case study research. Note: although many of the links cover the general category of qualitative research, all have sections that address issues of case studies.

• Sage Publications on Qualitative Methodology: Search here for a comprehensive list of new books being published about "Qualitative Methodology" http://www.sagepub.co.uk/
• The International Journal of Qualitative Studies in Education: An on-line journal "to enhance the theory and practice of qualitative research in education." On-line submissions are welcome. http://www.tandf.co.uk/journals/tf/09518398.html
• Qualitative Research Resources on the Internet: From syllabi to home pages to bibliographies. All links relate somehow to qualitative research. http://www.nova.edu/ssss/QR/qualres.html

Becker, Bronwyn, Patrick Dawson, Karen Devine, Carla Hannum, Steve Hill, Jon Leydens, Debbie Matuskevich, Carol Traver, & Mike Palmquist. (2005). Case Studies. Writing@CSU . Colorado State University. https://writing.colostate.edu/guides/guide.cfm?guideid=60

Organizing Your Social Sciences Research Assignments

• Annotated Bibliography
• Analyzing a Scholarly Journal Article
• Group Presentations
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

• The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
• The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
• The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
• The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
• The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

• What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
• Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
• What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
• How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

• Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
• Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
• Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
• Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
• Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
• Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
• Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

• If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
• If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

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• Communicable Diseases Module: Ethiopian Federal Ministry of Health
• Communicable Diseases Module: Acknowledgements
• Communicable Diseases Module: Introduction
• Communicable Diseases Module: 1. Basic Concepts in the Transmission of Communicable Diseases
• Communicable Diseases Module: 2. Prevention and Control of Communicable Diseases and Community Diagnosis
• Communicable Diseases Module: 3. Bacterial Vaccine-Preventable Diseases
• Communicable Diseases Module: 4. Viral Vaccine-Preventable Diseases
• Communicable Diseases Module: 5. Malaria Epidemiology and Transmission
• Communicable Diseases Module: 6. Factors that Affect Malaria Transmission
• Communicable Diseases Module: 7. Diagnosis of Malaria
• Communicable Diseases Module: 8. Malaria Case Management
• Communicable Diseases Module: 9. Malaria Prevention: Environmental Management and Larviciding for Vector Control
• Communicable Diseases Module: 10. Malaria Prevention: Indoor Residual Spraying of Houses
• Communicable Diseases Module: 11. Malaria Prevention: Insecticide Treated Nets
• Communicable Diseases Module: 12. Monitoring and Control of Malaria Epidemics
• Communicable Diseases Module: 13. Introduction, Transmission and Tuberculosis Case Finding
• Communicable Diseases Module: 14. Diagnosis and Treatment of Tuberculosis
• Communicable Diseases Module: 15. Follow-up of Patients on Anti-Tuberculosis Treatment and Defaulter Tracing
• Communicable Diseases Module: 16. Tuberculosis Treatment in Special Conditions: TB in Children, HIV/TB and Drug Resistant TB
• Communicable Diseases Module: 17. Tuberculosis Infection Control
• Communicable Diseases Module: 18. Leprosy Diagnosis
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• Communicable Diseases Module: 20. Introduction to HIV/AIDS
• Communicable Diseases Module: 21. Opportunistic Infections and WHO HIV Clinical Staging
• Communicable Diseases Module: 22. Introduction to Antiretroviral Therapy
• Communicable Diseases Module: 23. Adherence to HIV Care and Treatment
• Communicable Diseases Module: 24. Provider-Initiated HIV Testing and Counselling
• Communicable Diseases Module: 25. Prevention of HIV Infection, and Community Mobilisation
• Communicable Diseases Module: 26. Universal Precautions, Infection Prevention and Post-Exposure Prophylaxis for Health Workers
• Communicable Diseases Module: 27. Prevention of Mother-to-Child Transmission of HIV
• Communicable Diseases Module: 28. HIV in Children
• Communicable Diseases Module: 29. Positive Living and Prevention of HIV Transmission for PLHIV
• Communicable Diseases Module: 30. Providing Palliative Care for People Living with HIV
• Communicable Diseases Module: 31. Prevention and Control of Sexually Transmitted Infections
• Communicable Diseases Module: 32. General Features of Faeco-Orally Transmitted Diseases
• Communicable Diseases Module: 33. Bacterial and Viral Faeco-Oral Diseases
• Communicable Diseases Module: 34. Intestinal Protozoa, Ascariasis and Hookworm
• Communicable Diseases Module: 35. Acute Respiratory Tract Infections
• Communicable Diseases Module: 36. Louse-Borne Diseases: Relapsing Fever and Typhus
• Communicable Diseases Module: 37. Other Vector-Borne Diseases of Public Health Importance
• Communicable Diseases Module: 38. Common Zoonotic Diseases in Ethiopia: Rabies and Taeniasis
• Communicable Diseases Module: 39. Diseases of Poor Hygiene and Environmental Health: Trachoma, Scabies and Podoconiosis
• Communicable Diseases Module: 40. General Principles of Public Health Surveillance
• Introduction
• Learning Outcomes for Study Session 41
• 41.1  Importance of the Integrated Disease Surveillance and Response (IDSR) system
• 41.2  Priority diseases for IDSR in Ethiopia

41.3  Role of the Health Extension Practitioner in IDSR

41.4  Case definitions of priority diseases

• 41.5.1  Immediately reportable diseases
• 41.5.2  Weekly reportable diseases
• Summary of Study Session 41
• Self-Assessment Questions (SAQs) for Study Session 41
• Appendix 41.1  Modified case-based reporting form for immediately reportable diseases
• Appendix 41.2  Weekly Reporting Format for Health Extension Practitioners
• Communicable Diseases Module: 42. Epidemic Investigation and Management
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Communicable Diseases

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You learned in Study Session 40 that a case definition is a set of standard criteria used to help you to separate true cases (those with the disease) from suspected cases that do not have the disease. Health workers in hospitals and Health Centres should use standard case definitions for reporting suspected priority diseases, i.e. a definition that has been agreed and should be used by all health professionals at higher levels within the country. Standard case definitions should be applied in the same way to all the persons examined.

Standard case definitions classify cases as confirmed or suspected. A confirmed case shows all the typical symptoms of a disease and the infectious agent or other cause has been positively identified in a laboratory investigation. For example, in a confirmed case of malaria, the patient shows symptoms typical of malaria, such as fever, headache and joint pain, the rapid diagnostic test (RDT) is positive, and laboratory investigation of a blood smear has confirmed that the person is infected with the Plasmodium parasites that cause malaria (Figure 41.2). On the other hand, a suspected case of malaria means that the person shows symptoms of malaria, but a laboratory investigation either has not been conducted yet, or has failed to find evidence of the parasite that causes malaria.

A community case definition is a simplified version of the standard case definition, adapted to suit the needs and resources of Health Extension Practitioners/Workers, community health volunteers, community members, traditional healers and birth attendants. It is useful to make a poster showing these definitions for the Health Post wall in the local language. Table 41.3 summarises community case definitions for some of the priority diseases in Ethiopia.

As a Health Extension Practitioner, you need to teach the community about these community case definitions of common diseases (Figure 41.3). The community can recognise and report common diseases to you if they understand these case definitions. The advantage of using community case definitions (instead of standard case definitions) is not only that they are simpler to understand. They are also ‘broader’ than standard case definitions, which means that more suspected cases will be identified using the community case definition, and fewer cases will be missed.

41.5  Reporting of priority diseases

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-from the Epidemiological Bulletin, Vol. 20 No. 1, March 1999 -

Norms and Standards in Epidemiology: Case Definitions

The use of case definitions is very important in epidemiology in order to standardize criteria for identification of cases. All case definition must include the three classical dimensions of epidemiological variables: time , place and person. It is of foremost importance to precisely define what will be considered as a case, in order to accurately monitor the trends of reported diseases, to detect their unusual occurrences and, consequently, to evaluate the effectiveness of intervention. Thus, the usefulness of public health surveillance data depends on its uniformity, simplicity and timeliness.

According to the Dictionary of Epidemiology, edited for the International Epidemiological Association by John M. Last, a case in epidemiology, is a person in the population or study group identified as having the particular disease, health disorder, or condition under investigation. A variety of criteria may be used to identify cases, e.g. individual physician�s diagnoses, registries and notifications, abstracts of clinical records, surveys of the general population, and population screening, among others. The epidemiological definition of a case is not necessarily the same as the ordinary clinical definition.

In the United States, requirements for reporting diseases are mandated by state laws or regulations, even though the list of reportable diseases in each state differs. The Centers for Disease Control (CDC) have established a policy that requires state health departments to report cases of selected diseases to the CDC�s National Notifiable Diseases Surveillance System (NNDSS). However, before 1990, the usefulness of such data was limited by the lack of uniform case definitions for public health surveillance. There was no explicit criteria for identifying cases for public health surveillance purposes.

In October 1990, CDC published Case Definitions for Public Health Surveillance, which, for the first time, provided uniform criteria for reporting cases to increase the specificity of reporting and improve the comparability of diseases reported from different geographic areas.

In 1996, the CDC revised the list of diseases under epidemiological and public health surveillance, and published it as " Case Definitions for Infectious Conditions Under Public Health Surveillance" (MMWR 1997;46). The definition of terms used in this list for case classification is established as follows:

Clinically compatible case: a clinical syndrome generally compatible with the disease, as described in the clinical description.

Confirmed case: a case that is classified as confirmed for reporting purposes.

Epidemiologically linked case: a case in which (a) the patient has had contact with one or more persons who either have/had the disease or have been exposed to a point source of infection (i.e., a single source of infection, such as an event leading to a foodborne-disease outbreak, to which all confirmed case-patients were exposed) and (b) transmission of the agent by the usual modes of transmission is plausible. A case may be considered epidemiologically linked to a laboratory-confirmed case if at least one case in the chain of transmission is laboratory confirmed.

Laboratory-confirmed case: a case that is confirmed by one or more of the laboratory methods listed in the case definition under Laboratory Criteria for Diagnosis. Although other laboratory methods can be used in clinical diagnosis, only those listed are accepted as laboratory confirmation for national reporting purposes.

Probable case: a case that is classified as probable for reporting purposes.

Supportive or presumptive laboratory results: specified laboratory results that are consistent with the diagnosis, yet do not meet the criteria for laboratory confirmation.

Suspected case: a case that is classified as suspected for reporting purposes.

Since case definition is an important component of epidemiological surveillance, the Epidemiological Bulletin will publish periodically the CDC�s case definitions. This issue presents cholera, plague, and yellow fever, the three international quarantine diseases established by the International Health Regulations (1969), third annotated edition of 1983, which was updated and printed in 1992 by WHO. These diseases are also part of WHO�s epidemiological surveillance system.

CHOLERA (Revised September 1996)

Clinical Description: an illness characterized by diarrhea and/or vomiting; severity is variable.

Laboratory Criteria for Diagnosis

� Isolation of toxigenic (i.e., cholera toxin-producing) Vibrio cholerae O1 or O139 from stool or vomits, or

� Serologic evidence of recent infection

Case Classification

Confirmed: a clinically compatible illness that is laboratory confirmed

Comment: illnesses caused by strains of V. cholerae other than toxigenic V. cholerae O1 or O139 should not be reported as cases of cholera. The etiologic agent of a case of cholera should be reported as either V. cholerae O1 or V. cholerae O139. Only confirmed cases should be reported to NNDSS by state health departments.

PLAGUE (Revised September 1996)

Clinical description: plague is transmitted to humans by fleas or by direct exposure to infected tissues or respiratory droplets; the disease is characterized by fever, chills, headache, malaise, prostration, and leukocytosis that manifests in one or more of the following principal clinical forms:

� Regional lymphadenitis (bubonic plague);

� Septicemia without an evident bubo (septicemic plague);

� Plague pneumonia, resulting from hematogenous spread in bubonic or septicemic cases (secondary pneumonic plague), or inhalation of infectious droplets (primary pneumonic plague);

� Pharyngitis and cervical lymphadenitis resulting from exposure to larger infectious droplets or ingestion of infected tissues (pharyngeal plague).

Laboratory criteria for diagnosis

Presumptive:

� Elevated serum antibody titer(s) to Yersinia pestis

fraction 1 (F1) antigen (without documented fourfold

or greater change) in a patient with no history of plague vaccination, or

� Detection of F1 antigen in a clinical specimen by fluorescent assay.

Confirmatory:

� Isolation of Y. pestis from a clinical specimen, or

� Fourfold or greater change in serum antibody titer to Y. pestis F1 antigen.

Case classification

Suspected: a clinically compatible case without presumptive or confirmatory laboratory results

Probable: a clinically compatible case with presumptive laboratory results.

Confirmed: a clinically compatible case with confirmatory laboratory results.

YELLOW FEVER

Clinical description: a mosquito-borne viral illness characterized by acute onset and constitutional symptoms followed by a brief remission and a recurrence of fever, hepatitis, albuminuria, and symptoms and, in some instances, renal failure, shock, and generalized hemorrhages.

Laboratory criteria for diagnosis:

� Fourfold or greater rise in yellow fever antibody titer in a patient who has no history of recent yellow fever vaccination and cross-reactions to other flaviviruses have been excluded, or

� Demonstration of yellow fever virus, antigen, or genome in tissue, blood, or other body fluid.

Probable: a clinically compatible case with supportive serology (stable elevated antibody titer to yellow fever virus, e.g., greater than or equal to 32 by complement fixation, greater than or equal to 256 by immunofluorescence assay, greater than or equal to 320 by hemagglutination inhibition, greater than or equal to 160 by neutralization, or a positive serologic result by immunoglobulin M-capture enzyme immunoassay). Cross-reactive serologic reactions to other flaviviruses must be excluded, and the patient must not have a history of yellow fever vaccination.

Confirmed: a clinically compatible case that is laboratory confirmed.

Return to Index Epidemiological Bulletin, Vol. 20 No. 1, March 1999

Index of Online Bulletins

• Research article
• Open access
• Published: 17 January 2018

Health worker knowledge of Integrated Disease Surveillance and Response standard case definitions: a cross-sectional survey at rural health facilities in Kenya

• Mitsuru Toda   ORCID: orcid.org/0000-0002-5904-6658 1 ,
• Dejan Zurovac 2 , 3 ,
• Ian Njeru 4 ,
• David Kareko 4 ,
• Matilu Mwau 5 &
• Kouichi Morita 6  

BMC Public Health volume  18 , Article number:  146 ( 2018 ) Cite this article

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The correct knowledge of standard case definition is necessary for frontline health workers to diagnose suspected diseases across Africa. However, surveillance evaluations commonly assume this prerequisite. This study assessed the knowledge of case definitions for health workers and their supervisors for disease surveillance activities in rural Kenya.

A cross-sectional survey including 131 health workers and their 11 supervisors was undertaken in two counties in Kenya. Descriptive analysis was conducted to classify the correctness of knowledge into four categories for three tracer diseases (dysentery, measles, and dengue). We conducted a univariate and multivariable logistic regression analyses to explore factors influencing knowledge of the case definition for dysentery.

Among supervisors, 81.8% knew the correct definition for dysentery, 27.3% for measles, and no correct responses were provided for dengue. Correct knowledge was observed for 50.4% of the health workers for dysentery, only 12.2% for measles, and none for dengue. Of 10 examined factors, the following were significantly associated with health workers’ correct knowledge of the case definition for dysentery: health workers’ cadre (aOR 2.71; 95% CI 1.20–6.12; p  = 0.017), and display of case definition poster (aOR 2.24; 95% CI 1.01–4.98; p  = 0.048). Health workers’ exposure to the surveillance refresher training, supportive supervision and guidelines were not significantly associated with the knowledge.

The correct knowledge of standard case definitions was sub-optimal among health workers and their supervisors, which is likely to impact the reliability of routine surveillance reports generated from health facilities.

Peer Review reports

The first step in disease surveillance for frontline health workers is to diagnose and identify cases at health facilities. Rural health facilities in sub-Saharan Africa lack capacities to diagnose diseases through laboratory confirmations and health workers rely on clinical signs and symptoms to diagnose suspected cases of priority diseases. Validated clinical standard case definitions help standardize diagnosis of suspected cases across health workers within and across nations, and it is crucial for implementing the International Health Regulations 2005 [ 1 , 2 , 3 ]. In addition, standard case definitions are important for managers at all levels to monitor epidemic trends across health facilities, investigate epidemic alerts, respond to potential outbreaks, and plan activities related to disease surveillance and control.

In Kenya as in other African countries, the World Health Organization regional office for Africa (WHO-Afro) implemented the Integrated Disease Surveillance and Response (IDSR) strategy [ 4 , 5 ], which promotes the use of IDSR standard case definitions which are stipulated in technical guidelines, promoted through job aids, and included in the in-service training programs. In IDSR evaluation literature, processes of disease surveillance and activities supporting implementation have commonly been examined [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. However, the knowledge of IDSR standard case definitions by health workers and their supervisors have been assumed and no study has examined the awareness and knowledge of case definitions as stipulated in the guidelines [ 18 , 19 ]. We therefore conducted a cross-sectional study among frontline health workers and their disease surveillance supervisors in rural Kenya to assess their knowledge of IDSR standard case definitions.

A cross-sectional survey was conducted as part of the mSOS (mobile Short-message-service based disease Outbreak alert Systems) trial [ 20 ], which measured the effectiveness of an intervention using text-message disease outbreak alert system. The study took place at rural health facilities and sub-county management offices in Busia and Kajiado counties in Kenya.

Description of study area

Busia County is by the Victoria Lake basin and borders Uganda, and Kajiado County borders Tanzania. In the two counties, there are 143 functional health facilities belonging to 11 sub-counties. All health facilities are expected to report priority diseases through IDSR strategy to disease surveillance coordinators at the sub-county level. IDSR strategy was introduced to health workers in the two counties in 2005. Health facility in-charges, or IDSR focal persons at each health facility are required to send routine paper-based reports on priority diseases to sub-county office on immediate and weekly basis. Sub-county level disease surveillance coordinators are expected to monitor disease trends, respond to alerts of disease surveillance activities, and provide support supervision to the health facilities. Use of standard case definition has been promoted through the IDSR strategy in the area for over a decade. In addition, in September and October 2013, health facility in-charges in the study area attended an IDSR refresher training organized by the Ministry of Health. During the 1-day training, IDSR case definitions and reporting requirements were highlighted. Each participant was given the IDSR technical guidelines for use at their health facility, and participants were expected to have refreshed their knowledge on IDSR standard case definitions.

Participants and data collection

Of 143 health facilities, 12 health facilities were excluded from the study because the facilities were closed on the day of the survey. Participants included 131 health facility in-charges and 11 sub-county disease surveillance coordinators who were interviewed by the study team in April 2014, which was 6 months after the IDSR refresher training took place in the study area. Open-ended questionnaires were self-administered by health facility in-charge and their sub-county supervisors at their respective workstations on their knowledge of IDSR standard case definitions. The questionnaires were pre-tested in Nairobi prior to study collection. National level Ministry of Health staff members at the Disease Surveillance and Response Unit, who are well experienced and trained in IDSR strategy, supervised the collection of data at each study facility. The responses were recorded in English because it is the language for pre- and in- service trainings in Kenya.

Selection of tracer diseases and study definition

Three tracer diseases, dysentery, measles and dengue, were selected for analysis based on the epidemiological interest [ 21 ] and the complexity of the IDSR standard case definitions (Table  1 ). Dysentery was selected because the disease occurs frequently [ 22 , 23 , 24 ] and has only 2 simple key components in the case definition. Measles was selected because there are sporadic outbreaks in the country [ 25 , 26 ] and has slightly more complex case definition than dysentery containing 5 key components. Dengue was selected because the disease is reported frequently in the research setting [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ] and has a complex case definition containing 8 key components. All of the three tracer diseases require weekly reporting according to the national IDSR guidelines, while measles and dengue are also required to be reported immediately through the case-based reports as suspected cases are detected. Table 1 presents study definitions for each of the three tracer diseases by four categorization of the correctness: correct, partially correct, incorrect, and “do not know”. Responses were classified as correct when all key components were stated without other signs or symptoms. Partial correctness was defined as mentioning all of the key components, or mentioning some of key components with additional disease related symptoms. Incorrect responses were defined as mentioning only one or none of the key components. Finally, the last category “do not know” included answers where respondents did not mention any signs or symptoms.

Data analysis

Data were double entered using Base (LibreOffice 5, The Document Foundation, Berlin, Germany). Study investigators verified data manually comparing paper based questionnaires. During the coding process, we classified key words of signs and symptoms according to our study definitions for the three tracer diseases. Certain key words were included as synonyms, such as diarrhea and watery stool; eye discharge, red eyes and conjunctivitis; funny nose and coryza; pain in the eyes and retro-orbital pain; general pain, muscle pain and myalgia; joint pain and arthralgia; and low blood cells and leukopenia.

Descriptive analysis of IDSR standard case definition was conducted to categorize the correctness of knowledge of three tracer diseases. To explore factors influencing the knowledge of IDSR standard case definition, we focused on dysentery because the variability of correct responses was observed only for this tracer disease. We first conducted a univariate analysis and estimated odds ratios (OR), p -values, and 95% confidence intervals (CIs) for the association between 10 broad factors and correct dysentery knowledge outcome. The 10 factors included health worker and health facility characteristics. In specific, location and size of facility (dispensaries: government funded health facility that provides primary healthcare services, maternity homes: private or NGO funded health facility that cares for pregnant women, medical clinics: private health facility that provides primary healthcare services, and nursing homes: private or NGO funded health facility that cares for the elderly), availability of IDSR focal person at facility, age, gender, qualification (nurses: licensed medical practitioner with 3–4 years of pre-service training, clinical officer: licensed medical practitioner with 3–4 years of pre-service training, and medical doctor: licensed medical practitioner with 6 years of pre-service training), and exposure to IDSR interventions by health workers. Factors with p -value <0.2 were then entered into multivariable model. We also explored two-way interaction terms of 4 variables related to disease surveillance interventions. The variables were: exposure to training, availability of guidelines, availability of poster, and support supervision. None of these 4 factors in the interaction terms were statistically significant at 0.05 level and we did not include the interaction terms in the model. Analysis was performed using Stata version 14 (StataCorp, College Station, TX, USA). Hypothesis testing and CI estimation were completed with alpha level of 0.05.

Characteristics of health workers and their supervisors

Of 11 supervisors interviewed, 7 were from Busia (64.6%). All were public health officers. Nearly all disease surveillance coordinators were male (90.9%) and the median age of the coordinators was 44 years [IQR 38–46]. Of 131 respondents (Table  2 ), nearly 40 % were from Busia (36.6%). Most commonly, they worked at dispensaries (70.2%). Nearly two-thirds (64.1%) worked at government-owned public facilities, and over two-thirds (69.5%) worked at health facilities with an IDSR focal person. Half of the respondents were female (51.9%) and the median age of the respondents was 36 years [IQR 30–48]. The majority were nurses (70.2%). Around 20 % were clinical officers, who are clinicians with 3 years of pre-service training (20.6%). Regarding the surveillance related interventions, over two-thirds (68.7%) had IDSR case definition poster displayed, observed by study data collectors. Most of the respondents (74.1%) had received at least one support supervision visit on surveillance related matters in the past 6 months. Finally, only 15.3% had access to IDSR technical guidelines at their facility, while the majority (61.1%) attended the IDSR refresher training conducted by the study team 6 months earlier (Table 2 ).

Knowledge of IDSR case definitions

Table  3 describes the knowledge of three tracer diseases by health workers and their supervisors. Of 11 supervisors, 81.8% knew the correct definition for dysentery, 27.3% for measles, and no correct responses were provided for dengue. For measles, 36.4% responded partially correctly and 27.3% incorrectly. For dengue, only one supervisor provided partially correct response (9.1%), nearly half responded incorrectly (45.5%), and the remaining 45.5% did not know the definition (Table 3 ).

Health workers displayed similar patterns as their supervisors across the three tracer diseases. Correct knowledge was observed for 50.4% of the health workers for dysentery, for only 12.2% for measles, and none of the health workers provided correct case definition for dengue. For dysentery, 17.6% responded partially correctly where bloody diarrhea was mentioned but also additional dysentery related signs and symptoms such as pain or cramps (11/23) and fever (3/23). Furthermore, twenty-two health workers (16.8%) provided incorrect case definitions by either omitting diarrhea (16/22) or blood (6/22). Finally, the remaining 20 health workers (15.3%) did not know the definition for dysentery (Table 3 ).

For measles, less than half of health workers responded partially correctly (41.2%) where health workers were able to mention fever and rash, but not all of the additional three components (cough, coryza, and conjunctivitis). Most commonly omitted symptoms were cough (37/54), followed by coryza (29/54), and conjunctivitis (12/54). Over one-quarter of health workers responded incorrectly (27.5%) by omitting fever (29/36) followed by rash (12/36). The remaining 19.1% of the health workers did not know the case definition for measles (Table 3 ).

Nearly all (96.2%) health workers either incorrectly stated or did not know the case definition for dengue. Among the incorrect responses, three did not mention fever (3/41), while other dengue criteria were rarely mentioned: headache (9/41), arthralgia (8/41), hemorrhagic manifestations (6/41), retro-orbital pain (2/41), and rash (2/41), myalgia (0/41), and leukopenia (0/41).

Predictors influencing knowledge of dysentery

We examined 10 factors that may influence the health facility in-charges’ knowledge of dysentery. The following variables did not meet entrance criteria ( p  < 0.2) for the multivariable analysis: county (OR 1.11; 95% CI 0.55–2.27; p  = 0.767), smaller facilities (OR 1.47; 95% CI 0.69–3.13, p  = 0.313), age (OR 1.23; 95% CI 0.62–2.47; p  = 0.553), gender (OR 1.09; 95% CI 0.55–2.17; p  = 0.796), training (OR 1.41; 95% CI 0.70–2.86; p  = 0.335), presence of IDSR technical guidelines (OR 0.61; 95% CI 0.23–1.61; p  = 0.316), and support supervision (OR 0.87; 95% CI 0.40–1.90; p  = 0.729) (Table  4 ). The following factors were significantly associated with correct dysentery IDSR standard case definition knowledge in the multivariable analysis: health workers’ cadre (aOR 2.71; 95% CI 1.20–6.12; p  = 0.017), and display of case definition poster (aOR 2.24; 95% CI 1.01–4.98; p  = 0.048). Although meeting the inclusion criteria for multivariable model, the presence of IDSR focal person at the health facility (aOR 1.83; 95% CI 0.82–4.09; p  = 0.139) was not significantly associated with correct dysentery knowledge (Table 4 ).

Correct knowledge of standard case definitions is an important first step for successful implementation of any disease surveillance strategy. Our study, one of the first that examined and quantified the knowledge of IDSR standard case definitions in sub-Saharan Africa, revealed alarmingly low levels of knowledge in Kenya. Patient registers at health facilities are used as source document for evaluating disease surveillance reporting practices and health systems in general [ 35 ], and our study findings imply that the validity of the source documents may be overlooked. First, we found that knowledge of dengue is practically non-existent among health workers and their disease surveillance supervisors. We speculate that the relatively complex case definitions, lack of routine laboratory diagnosis to confirm dengue in rural health facilities, similarities with other mosquito-borne diseases such as malaria, and the possibility of perceived non-lethal nature of the disease may contribute to low knowledge. The findings are however not unique to our study sites since suboptimal knowledge of dengue has also been reported among health workers in high-income countries [ 36 ]. Similarly to dengue but even more surprising finding was found with respect to measles. Despite simple case definitions, only a quarter of supervisors and just one in ten health workers could state five clinical criteria, which have been promoted in Kenya over a decade. It should also be acknowledged that surveillance guidelines in Kenya include an ambiguous and unnecessary wording, “any person in whom a clinician suspects measles”, which undermines the validity of promoted case definitions and itself precludes standardization. Similar sentiments were expressed in an evaluation conducted in South Sudan [ 37 ]. The most unexpected finding was observed on dysentery where only half of the health workers were able to correctly state the simple criteria of “bloody diarrhea.” Health workers responses of other dysentery related symptoms such as “abdominal cramps and pains” may suggest the health workers are knowledgeable of the text book clinical features [ 38 ], but disregarding the IDSR guidelines.

Our predictor analysis examining factors for correct knowledge added further light on what may influence knowledge of dysentery. First, we found that nurses are significantly more knowledgeable compared to other cadres of health workers. One of the possible explanations is that health workers with greater pre-service clinical training are more likely to overrule guidelines, which has been shown in previous studies [ 39 , 40 ]. Second, the presence of a simple job aid in the form of a case definition poster at a health facility was significantly associated with better knowledge. Reminders are shown to be effective intervention in other studies [ 41 ], and policy makers should prioritize such seemingly simple intervention. In addition, this study was conducted in the context of evaluating a text message intervention to enhance disease surveillance reporting [ 20 ] and reminder interventions through such channels but targeting health workers should also be explored in the future. Finally, exposure to either refresher training or supervision was not associated with greater knowledge of case definition. We do not think that these interventions are ineffective per se, but perhaps the sub-optimal quality of the training and supervision intervention may have contributed to the analysis results. The study did not have a component to measure the quality of training or resources to follow-up supervision mechanisms after training, but we speculate that these factors may have contributed to low knowledge levels. Moreover, the low knowledge levels of disease surveillance supervisors found in this study further elevates the levels of challenges faced in the field to promote adherence to IDSR standard case definitions.

Several study limitations should be acknowledged. First, the knowledge levels were self-reported by health workers and the study did not examine whether the health workers’ knowledge was translated into practice. We also did not examine the duration of professional experience that may have influenced the level of knowledge. Knowledge is however a prerequisite for correct practice and it is unlikely that health workers would adhere to guidelines. We also cannot confidently assume uniformity in diagnosis of suspected cases when knowledge of the standard case definition is not present. Second, we limited the analysis to three tracer diseases and applied a rather relaxed approach to interpreting the definitions. Given the low knowledge levels found overall in the study, stricter case definitions would have however yielded even lower knowledge results, and likely without changes to the interpretation of the findings. Third, the small sample size used in this study may have precluded showing significant associations when associations were truly present, and results should be interpreted with caution. Finally, while the study included a number of health workers from two areas in Kenya, the results are not nationally representative and cannot be generalized across the country.

Overall, the IDSR case definition knowledge needs to be further improved among both health workers and their supervisors, and the findings are likely to impact the reliability of routine surveillance reports generated from health facilities. The findings also suggest that simple intervention such as reminders are more effective than ad hoc trainings and routine supervision to ensure uniformed knowledge of case definitions. Further studies on examining effective methods of enhancing knowledge of IDSR standard case definitions are justified.

Baker MG, Fidler DP. Global public health surveillance under new international health regulations. Emerg Infect Dis. 2006;12:1058–65.

Article   PubMed   PubMed Central   Google Scholar  

Fidler DP, Gostin LO. The new international health regulations: an historic development for international law and public health. J Law Med Ethics. 2006;34(85–94):84.

Google Scholar  

Kasolo F, Yoti Z, Bakyaita N, Gaturuku P, Katz R, et al. IDSR as a platform for implementing IHR in African countries. Biosecur Bioterror. 2013;11:163–9.

Ministry of Public Health and Sanitation (2012) Integrated disease surveillance and response in Kenya: technical guidelines 2012.

Perry HN, McDonnell SM, Alemu W, Nsubuga P, Chungong S, et al. Planning an integrated disease surveillance and response system: a matrix of skills and activities. BMC Med. 2007;5:24.

Sow I, Alemu W, Nanyunja M, Duale S, Perry HN, et al. Trained district health personnel and the performance of integrated disease surveillance in the WHO African region. East Afr J Public Health. 2010;7:16–9.

PubMed   Google Scholar  

Adokiya MN, Awoonor-Williams JK, Barau IY, Beiersmann C, Mueller O. Evaluation of the integrated disease surveillance and response system for infectious diseases control in northern Ghana. BMC Public Health. 2015;15:75.

Adokiya MN, Awoonor-Williams JK, Beiersmann C, Muller O. The integrated disease surveillance and response system in northern Ghana: challenges to the core and support functions. BMC Health Serv Res. 2015;15:288.

Adokiya MN, Awoonor-Williams JK, Beiersmann C, Muller O. Evaluation of the reporting completeness and timeliness of the integrated disease surveillance and response system in northern Ghana. Ghana Med J. 2016;50:3–8.

Lukwago L, Nanyunja M, Ndayimirije N, Wamala J, Malimbo M, et al. The implementation of integrated disease surveillance and response in Uganda: a review of progress and challenges between 2001 and 2007. Health Policy Plan. 2013;28:30–40.

Article   PubMed   Google Scholar  

Phalkey RK, Kroll M, Dutta S, Shukla S, Butsch C, et al. Knowledge, attitude, and practices with respect to disease surveillance among urban private practitioners in Pune, India. Glob Health Action. 2015;8:28413.

McDonnell SM, Perry HN, McLaughlin B, McCurdy B, Parrish RG. Information for disasters, information disasters, and disastrous information. Prehosp Disaster Med. 2007;22:406–13.

Mwatondo AJ, Ng'ang'a Z, Maina C, Makayotto L, Mwangi M, et al. Factors associated with adequate weekly reporting for disease surveillance data among health facilities in Nairobi County, Kenya, 2013. Pan Afr Med J. 2016;23:165.

Nnebue CC, Onwasigwe CN, Adogu PO, Onyeonoro UU. Awareness and knowledge of disease surveillance and notification by health-care workers and availability of facility records in Anambra state, Nigeria. Niger Med J. 2012;53:220–5.

Nnebue CC, Onwasigwe CN, Ibeh CC, Adogu PO. Effectiveness of data collection and information transmission process for disease notification in Anambra state, Nigeria. Niger J Clin Pract. 2013;16:483–9.

Article   CAS   PubMed   Google Scholar  

Nsubuga P, Brown WG, Groseclose SL, Ahadzie L, Talisuna AO, et al. Implementing integrated disease surveillance and response: four African countries’ experience, 1998-2005. Glob Public Health. 2010;5:364–80.

Nsubuga P, Eseko N, Tadesse W, Ndayimirije N, Stella C, et al. Structure and performance of infectious disease surveillance and response, United Republic of Tanzania, 1998. Bull World Health Organ. 2002;80:196–203.

PubMed   PubMed Central   Google Scholar  

Phalkey RK, Yamamoto S, Awate P, Marx M. Challenges with the implementation of an integrated disease surveillance and response (IDSR) system: systematic review of the lessons learned. Health Policy Plan. 2015;30(1):131–43.

Sahal N, Reintjes R, Aro AR. Review article: communicable diseases surveillance lessons learned from developed and developing countries: literature review. Scand J Public Health. 2009;37:187–200.

Toda M, Njeru I, Zurovac D, Tipo SO, Kareko D, et al. Effectiveness of a mobile short-message-service-based disease outbreak alert system in Kenya. Emerg Infect Dis. 2016;22:711–5.

Kebede S, Duales S, Yokouide A, Alemu W. Trends of major disease outbreaks in the African region, 2003-2007. East African journal of public health. 2010;7:20–9.

Njuguna C, Njeru I, Mgamb E, Langat D, Makokha A, et al. Enteric pathogens and factors associated with acute bloody diarrhoea, Kenya. BMC Infect Dis. 2016;16:477.

Pavlinac PB, Denno DM, John-Stewart GC, Onchiri FM, Naulikha JM, et al. Failure of syndrome-based diarrhea management guidelines to detect Shigella infections in Kenyan children. J Pediatric Infect Dis Soc. 2016;5:366–74.

Livio S, Strockbine NA, Panchalingam S, Tennant SM, Barry EM, et al. Shigella isolates from the global enteric multicenter study inform vaccine development. Clin Infect Dis. 2014;59:933–41.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Centers for Disease C, Prevention. Measles--horn of Africa, 2010-2011. MMWR Morb Mortal Wkly Rep. 2012;61:678–84.

Navarro-Colorado C, Mahamud A, Burton A, Haskew C, Maina GK, et al. Measles outbreak response among adolescent and adult Somali refugees displaced by famine in Kenya and Ethiopia, 2011. J Infect Dis. 2014;210:1863–70.

Were F. The dengue situation in Africa. Paediatr Int Child Health. 2012;32(Suppl 1):18–21.

Blaylock JM, Maranich A, Bauer K, Nyakoe N, Waitumbi J, et al. The seroprevalence and seroincidence of dengue virus infection in western Kenya. Travel Med Infect Dis. 2011;9:246–8.

Sutherland LJ, Cash AA, Huang YJ, Sang RC, Malhotra I, et al. Serologic evidence of arboviral infections among humans in Kenya. Am J Trop Med Hyg. 2011;85:158–61.

Mease LE, Coldren RL, Musila LA, Prosser T, Ogolla F, et al. Seroprevalence and distribution of arboviral infections among rural Kenyan adults: a cross-sectional study. Virol J. 2011;8:371.

Konongoi L, Ofula V, Nyunja A, Owaka S, Koka H, et al. Detection of dengue virus serotypes 1, 2 and 3 in selected regions of Kenya: 2011-2014. Virol J. 2016;13:182.

Baba M, Villinger J, Masiga DK. Repetitive dengue outbreaks in East Africa: a proposed phased mitigation approach may reduce its impact. Rev Med Virol. 2016;26:183–96.

Lutomiah J, Barrera R, Makio A, Mutisya J, Koka H, et al. Dengue outbreak in Mombasa City, Kenya, 2013-2014: entomologic investigations. PLoS Negl Trop Dis. 2016;10:e0004981.

Ngoi CN, Price MA, Fields B, Bonventure J, Ochieng C, et al. Dengue and Chikungunya virus infections among young febrile adults evaluated for acute HIV-1 infection in coastal Kenya. PLoS One. 2016;11:e0167508.

Amoakoh-Coleman M, Kayode GA, Brown-Davies C, Agyepong IA, Grobbee DE, et al. Completeness and accuracy of data transfer of routine maternal health services data in the greater Accra region. BMC Res Notes. 2015;8:114.

Adam JK, Abeyta R, Smith B, Gaul L, Thomas DL, et al. Clinician survey to determine knowledge of dengue and clinical management practices, Texas, 2014. Am J Trop Med Hyg. 2017;96(3):708–14.

Pond B, Sakka HE, Wamala J, Lukwago L. Mid-term evaluation of the integrated disease surveillance and response project. Manage Syst Int. 2011; http://pdf.usaid.gov/pdf_docs/Pdact326.pdf .

Christopher PR, David KV, John SM, Sankarapandian V. Antibiotic therapy for Shigella dysentery. Cochrane Database Syst Rev. 2010;(8):CD006784.

Zurovac D, Guintran JO, Donald W, Naket E, Malinga J, et al. Health systems readiness and management of febrile outpatients under low malaria transmission in Vanuatu. Malar J. 2015;14:489.

Steinhardt LC, Onikpo F, Kouame J, Piercefield E, Lama M, et al. Predictors of health worker performance after integrated Management of Childhood Illness training in Benin: a cohort study. BMC Health Serv Res. 2015;15:276.

Knebel E, Lundahl S, Raj HA, Ashton J, Wilson N. The use of manual job aids by health care providers: what do we know? Qual Assur Proj. 2000; https://www.usaidassist.org/sites/assist/files/use_of_job_aids_qap_2000.pdf .

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Acknowledgements

We thank the Disease Surveillance and Response Unit at the Ministry of Health in Kenya for their support on this study. We also thank the Kajiado and Busia County governments and the disease surveillance coordinators in the sub counties for their support. We are also grateful for the field interviewers and research assistants for their tireless work. This study is published with the permission of the Director of KEMRI.

The Japan International Cooperation Agency (JICA) and the Japan Agency for Medical Research and Development (AMED) supported this study under the Science and Technology Research Partnerships (SATREPS) project in Kenya (2012–2017). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Conceived and designed experiments: MT DZ IN MM KM. Performed experiments: MT DK IN. Analyzed the data: MT DZ. Contributed to analysis tools: MT DZ DK IN. Wrote the paper: MT DZ DK IN MM KM. Critically reviewed the paper and approved the final version: MT DZ DK IN MM KM. All authors read and approved the final manuscript.

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Toda, M., Zurovac, D., Njeru, I. et al. Health worker knowledge of Integrated Disease Surveillance and Response standard case definitions: a cross-sectional survey at rural health facilities in Kenya. BMC Public Health 18 , 146 (2018). https://doi.org/10.1186/s12889-018-5028-2

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Lesson 1: Introduction to Epidemiology

Section 5: the epidemiologic approach.

As with all scientific endeavors, the practice of epidemiology relies on a systematic approach. In very simple terms, the epidemiologist:

• Counts cases or health events, and describes them in terms of time, place, and person;
• Divides the number of cases by an appropriate denominator to calculate rates; and
• Compares these rates over time or for different groups of people.

Before counting cases, however, the epidemiologist must decide what a case is. This is done by developing a case definition. Then, using this case definition, the epidemiologist finds and collects information about the case-patients. The epidemiologist then performs descriptive epidemiology by characterizing the cases collectively according to time, place, and person. To calculate the disease rate, the epidemiologist divides the number of cases by the size of the population. Finally, to determine whether this rate is greater than what one would normally expect, and if so to identify factors contributing to this increase, the epidemiologist compares the rate from this population to the rate in an appropriate comparison group, using analytic epidemiology techniques. These epidemiologic actions are described in more detail below. Subsequent tasks, such as reporting the results and recommending how they can be used for public health action, are just as important, but are beyond the scope of this lesson.

Defining a case

Before counting cases, the epidemiologist must decide what to count, that is, what to call a case. For that, the epidemiologist uses a case definition. A case definition is a set of standard criteria for classifying whether a person has a particular disease, syndrome, or other health condition. Some case definitions, particularly those used for national surveillance, have been developed and adopted as national standards that ensure comparability. Use of an agreed-upon standard case definition ensures that every case is equivalent, regardless of when or where it occurred, or who identified it. Furthermore, the number of cases or rate of disease identified in one time or place can be compared with the number or rate from another time or place. For example, with a standard case definition, health officials could compare the number of cases of listeriosis that occurred in Forsyth County, North Carolina in 2000 with the number that occurred there in 1999. Or they could compare the rate of listeriosis in Forsyth County in 2000 with the national rate in that same year. When everyone uses the same standard case definition and a difference is observed, the difference is likely to be real rather than the result of variation in how cases are classified.

To ensure that all health departments in the United States use the same case definitions for surveillance, the Council of State and Territorial Epidemiologists (CSTE), CDC, and other interested parties have adopted standard case definitions for the notifiable infectious diseases.( 25 ) These definitions are revised as needed. In 1999, to address the need for common definitions and methods for state-level chronic disease surveillance, CSTE, the Association of State and Territorial Chronic Disease Program Directors, and CDC adopted standard definitions for 73 chronic disease indicators.( 29 )

Other case definitions, particularly those used in local outbreak investigations, are often tailored to the local situation. For example, a case definition developed for an outbreak of viral illness might require laboratory confirmation where such laboratory services are available, but likely would not if such services were not readily available.

Components of a case definition for outbreak investigations

A case definition consists of clinical criteria and, sometimes, limitations on time, place, and person. The clinical criteria usually include confirmatory laboratory tests, if available, or combinations of symptoms (subjective complaints), signs (objective physical findings), and other findings. Case definitions used during outbreak investigations are more likely to specify limits on time, place, and/or person than those used for surveillance. Contrast the case definition used for surveillance of listeriosis (see box below) with the case definition used during an investigation of a listeriosis outbreak in North Carolina in 2000.( 25 , 26 )

Both the national surveillance case definition and the outbreak case definition require a clinically compatible illness and laboratory confirmation of Listeria monocytogenes from a normally sterile site, but the outbreak case definition adds restrictions on time and place, reflecting the scope of the outbreak.

Listeriosis — Surveillance Case Definition

Clinical description

Infection caused by Listeria monocytogenes , which may produce any of several clinical syndromes, including stillbirth, listeriosis of the newborn, meningitis, bacteriemia, or localized infections

Laboratory criteria for diagnosis

Isolation of L. monocytogenes from a normally sterile site (e.g., blood or cerebrospinal fluid or, less commonly, joint, pleural, or pericardial fluid)

Case classification

Confirmed : a clinically compatible case that is laboratory confirmed

Source: Centers for Disease Control and Prevention. Case definitions for infectious conditions under public health surveillance. MMWR Recommendations and Reports 1997:46(RR-10):49-50.

Listeriosis — Outbreak Investigation

Case definition

Clinically compatible illness with L. monocytogenes isolated

• From a normally sterile site
• In a resident of Winston-Salem, North Carolina
• With onset between October 24, 2000 and January 4, 2001

Source: MacDonald P, Boggs J, Whitwam R, Beatty M, Hunter S, MacCormack N, et al. Listeria-associated birth complications linked with homemade Mexican-style cheese, North Carolina, October 2000 [abstract]. 50th Annual Epidemic Intelligence Service Conference; 2001 Apr 23–27; Atlanta, GA.

Many case definitions, such as that shown for listeriosis, require laboratory confirmation. This is not always necessary, however; in fact, some diseases have no distinctive laboratory findings. Kawasaki syndrome, for example, is a childhood illness with fever and rash that has no known cause and no specifically distinctive laboratory findings. Notice that its case definition (see box below) is based on the presence of fever, at least four of five specified clinical findings, and the lack of a more reasonable explanation.

Kawasaki Syndrome — Case Definition

A febrile illness of greater than or equal to 5 days’ duration, with at least four of the five following physical findings and no other more reasonable explanation for the observed clinical findings:

• Bilateral conjunctival injection
• Oral changes (erythema of lips or oropharynx, strawberry tongue, or fissuring of the lips)
• Peripheral extremity changes (edema, erythema, or generalized or periungual desquamation)
• Cervical lymphadenopathy (at least one lymph node greater than or equal to 1.5 cm in diameter)

Confirmed : a case that meets the clinical case definition

Comment : If fever disappears after intravenous gamma globulin therapy is started, fever may be of less than 5 days’ duration, and the clinical case definition may still be met.

Source: Centers for Disease Control and Prevention. Case definitions for infectious conditions under public health surveillance. MMWR Recommendations and Reports 1990:39(RR-13):18.

Criteria in case definitions

A case definition may have several sets of criteria, depending on how certain the diagnosis is. For example, during an investigation of a possible case or outbreak of measles, a person with a fever and rash might be classified as having a suspected, probable, or confirmed case of measles, depending on what evidence of measles is present (see box below).

Measles (Rubeola) — 1996 Case Definition

An illness characterized by all the following:

• A generalized rash lasting greater than or equal to 3 days
• A temperature greater than or equal to 101.0°F (greater than or equal to 38.3°C)
• Cough, coryza, or conjunctivitis
• Positive serologic test for measles immunoglobulin M antibody, or
• Significant rise in measles antibody level by any standard serologic assay, or
• Isolation of measles virus from a clinical specimen

Comment: Confirmed cases should be reported to National Notifiable Diseases Surveillance System. An imported case has its source outside the country or state. Rash onset occurs within 18 days after entering the jurisdiction, and illness cannot be linked to local transmission. Imported cases should be classified as:

• International. A case that is imported from another country
• Out-of-State. A case that is imported from another state in the United States. The possibility that a patient was exposed within his or her state of residence should be excluded; therefore, the patient either must have been out of state continuously for the entire period of possible exposure (at least 7-18 days before onset of rash) or have had one of the following types of exposure while out of state: a) face-to-face contact with a person who had either a probable or confirmed case or b) attendance in the same institution as a person who had a case of measles (e.g., in a school, classroom, or day care center).

An indigenous case is defined as a case of measles that is not imported. Cases that are linked to imported cases should be classified as indigenous if the exposure to the imported case occurred in the reporting state. Any case that cannot be proved to be imported should be classified as indigenous.

Source: Centers for Disease Control and Prevention. Case definitions for infectious conditions under public health surveillance. MMWR Recommendations and Reports 1997:46(RR-10):23–24.

A case might be classified as suspected or probable while waiting for the laboratory results to become available. Once the laboratory provides the report, the case can be reclassified as either confirmed or “not a case,” depending on the laboratory results. In the midst of a large outbreak of a disease caused by a known agent, some cases may be permanently classified as suspected or probable because officials may feel that running laboratory tests on every patient with a consistent clinical picture and a history of exposure (e.g., chickenpox) is unnecessary and even wasteful. Case definitions should not rely on laboratory culture results alone, since organisms are sometimes present without causing disease.

Modifying case definitions

Case definitions can also change over time as more information is obtained. The first case definition for SARS, based on clinical symptoms and either contact with a case or travel to an area with SARS transmission, was published in CDC’s Morbidity and Mortality Weekly Report (MMWR) on March 21, 2003 (see box below).( 27 ) Two weeks later it was modified slightly. On March 29, after a novel coronavirus was determined to be the causative agent, an interim surveillance case definition was published that included laboratory criteria for evidence of infection with the SARS-associated coronavirus. By June, the case definition had changed several more times. In anticipation of a new wave of cases in 2004, a revised and much more complex case definition was published in December 2003.( 28 )

CDC Preliminary Case Definition for Severe Acute Respiratory Syndrome (SARS) — March 21, 2003

Suspected case

Respiratory illness of unknown etiology with onset since February 1, 2003, and the following criteria:

• Documented temperature > 100.4°F (>38.0°C)
• One or more symptoms with respiratory illness (e.g., cough, shortness of breath, difficulty breathing, or radiographic findings of pneumonia or acute respiratory distress syndrome)
• Close contact * within 10 days of onset of symptoms with a person under investigation for or suspected of having SARS or travel within 10 days of onset of symptoms to an area with documented transmission of SARS as defined by the World Health Organization (WHO)

* Defined as having cared for, having lived with, or having had direct contact with respiratory secretions and/or body fluids of a person suspected of having SARS.

Source: Centers for Disease Control and Prevention. Outbreak of severe acute respiratory syndrome–worldwide, 2003. MMWR 2003:52:226–8.

Variation in case definitions

Case definitions may also vary according to the purpose for classifying the occurrences of a disease. For example, health officials need to know as soon as possible if anyone has symptoms of plague or anthrax so that they can begin planning what actions to take. For such rare but potentially severe communicable diseases, for which it is important to identify every possible case, health officials use a sensitive case definition. A sensitive case definition is one that is broad or “loose,” in the hope of capturing most or all of the true cases. For example, the case definition for a suspected case of rubella (German measles) is “any generalized rash illness of acute onset.” ( 25 ) This definition is quite broad, and would include not only all cases of rubella, but also measles, chickenpox, and rashes due to other causes such as drug allergies. So while the advantage of a sensitive case definition is that it includes most or all of the true cases, the disadvantage is that it sometimes includes other illnesses as well.

On the other hand, an investigator studying the causes of a disease outbreak usually wants to be certain that any person included in a study really had the disease. That investigator will prefer a specific or “strict” case definition. For instance, in an outbreak of Salmonella Agona infection, the investigators would be more likely to identify the source of the infection if they included only persons who were confirmed to have been infected with that organism, rather than including anyone with acute diarrhea, because some persons may have had diarrhea from a different cause. In this setting, the only disadvantages of a strict case definition are the requirement that everyone with symptoms be tested and an underestimation of the total number of cases if some people with salmonellosis are not tested.

Exercise 1.4

Investigators of an outbreak of trichinosis used a case definition with the following categories:

Clinical Criteria

Using this case definition, assign the appropriate classification to each of the persons included in the line listing below. Use the highest rate classification possible. (All were residents of Atlanta with acute onset of symptoms in November.)

Check your answer.

Exercise 1.5

Consider the initial case definition for SARS presented (on page 1–26 in the book) . Explain how the case definition might address the purposes listed below.

• Diagnosing and caring for individual patients
• Tracking the occurrence of disease
• Doing research to identify the cause of the disease
• Deciding who should be quarantined (quarantine is the separation or restriction of movement of persons who are not ill but are believed to have been exposed to infection, to prevent further transmission)

Using counts and rates

As noted, one of the basic tasks in public health is identifying and counting cases. These counts, usually derived from case reports submitted by health-care workers and laboratories to the health department, allow public health officials to determine the extent and patterns of disease occurrence by time, place, and person. They may also indicate clusters or outbreaks of disease in the community.

Counts are also valuable for health planning. For example, a health official might use counts (i.e., numbers) to plan how many infection control isolation units or doses of vaccine may be needed.

However, simple counts do not provide all the information a health department needs. For some purposes, the counts must be put into context, based on the population in which they arose. Rates are measures that relate the numbers of cases during a certain period of time (usually per year) to the size of the population in which they occurred. For example, 42,745 new cases of AIDS were reported in the United States in 2002.( 30 ) This number, divided by the estimated 2002 population, results in a rate of 15.3 cases per 100,000 population. Rates are particularly useful for comparing the frequency of disease in different locations whose populations differ in size. For example, in 2003, Pennsylvania had over twelve times as many births (140,660) as its neighboring state, Delaware (11,264). However, Pennsylvania has nearly ten times the population of Delaware. So a more fair way to compare is to calculate rates. In fact, the birth rate was greater in Delaware (13.8 per 1,000 women aged 15–44 years) than in Pennsylvania (11.4 per 1,000 women aged 15–44 years).( 31 )

Rates are also useful for comparing disease occurrence during different periods of time. For example, 19.5 cases of chickenpox per 100,000 were reported in 2001 compared with 135.8 cases per 100,000 in 1991. In addition, rates of disease among different subgroups can be compared to identify those at increased risk of disease. These so-called high risk groups can be further assessed and targeted for special intervention. High risk groups can also be studied to identify risk factors that cause them to have increased risk of disease. While some risk factors such as age and family history of breast cancer may not be modifiable, others, such as smoking and unsafe sexual practices, are. Individuals can use knowledge of the modifiable risk factors to guide decisions about behaviors that influence their health.

References (This Section)

• Centers for Disease Control and Prevention. Case definitions for infectious conditions under public health surveillance. MMWR Recomm Rep 1997:46(RR-10):1–55.
• MacDonald P, Boggs J, Whitwam R, Beatty M, Hunter S, MacCormack N, et al. Listeria-associated birth complications linked with homemade Mexican-style cheese, North Carolina, October 2000 [abstract]. 50th Annual Epidemic Intelligence Service Conference; 2001 Apr 23–27; Atlanta, GA.
• Centers for Disease Control and Prevention. Outbreak of severe acute respiratory syndrome–worldwide, 2003. MMWR 2003: 52:226–8.
• Centers for Disease Control and Prevention. Revised U.S. surveillance case definition for severe acute respiratory syndrome (SARS) and update on SARS cases–United States and worldwide, December 2003. MMWR 2003:52:1202–6.
• Centers for Disease Control and Prevention. Indicators for chronic disease surveillance. MMWR Recomm Rep 2004;53(RR-11):1–6.
• Centers for Disease Control and Prevention. Summary of notifiable diseases–United States, 2001. MMWR 2001;50(53).

Outbreak Investigations

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Step 3: Establish a Case Definition; Identify Cases

Case definitions, example #1: cdc case definition for giardiasis, example #2: cdc case definitions for viral hepatitis, clinical criteria for a case definition, categories of cases: confirmed, probable, and possible cases, case finding.

All Modules

By a case definition we mean the standard criteria for categorizing an individual as a case. Establishing a case definition (the criteria that need to be met in order to be considered "a case") can be tricky, particularly in the initial phases of the investigation. You want your definition to specific enough to identify true cases of disease, but you also want it to be broad enough and sensitive enough that it will identify most, if not all of the cases. As a result, the case definition may change during the investigation. In the earliest stages, it might be broader and less specific in order to make sure you identify all of the potential cases ("possible" cases), but later on, it might include more specific clinical or laboratory criteria that enable you to categorize individuals as "probable" or "confirmed" cases.

Case definitions may include four types of information:

• clinical information such as symptoms or lab results, e.g. the presence of fever >101 o F and jaundice for hepatitis A or the presence of elevated IgM anti-HAV antibodies in an outbreak of hepatitis A
• personal characteristics of the cases, e.g., individuals in a certain age group
• limits with respect to the location of the case (e.g., residing or working on the South Shore of Massachusetts) 
• a specified time period for this particular outbreak (e.g., during February and March 2009 or among people who attended a specific  wedding)

The CDC also makes well established case definitions available:

•  CDC's Case Definitions for Infectious Conditions Under Public Health Surveillance
•  CDC's Case Definitions for Chemical Poisoning

Clinical description

An illness caused by the protozoan Giardia lamblia and characterized by diarrhea, abdominal cramps, bloating, weight loss, or malabsorption. Infected persons may be asymptomatic.

Laboratory criteria for diagnosis

• Demonstration of G. lamblia cysts in stool, or
• Demonstration of G. lamblia trophozoites in stool, duodenal fluid, or small bowel biopsy, or
• Demonstration of G. lamblia antigen in stool by a specific immunodiagnostic test such as enzyme-linked immunosorbent assay (ELISA)

Case classification

Clinical case definition

An illness with a) discrete onset of symptoms and b) jaundice or elevated serum aminotransferase levels

• Hepatitis A: IgM anti-HAV-positive
• Hepatitis B: IgM anti-HBc-positive (if done) or HBsAg-positive, and IgM anti-HAV negative (if done)
• Non-A, Non-B Hepatitis:
• IgM anti-HAV-negative, and
• IgM anti-HBc-negative (if done) or HBsAg-negative, and
• Serum aminotransferase levels >2 1/2 times the upper limit of normal
• Delta Hepatitis: HBsAg- or IgM anti-HBc-positive and anti-HDV-positive

Comment: A serologic test for IgG antibody to the recently described hepatitis C virus is available, and many cases of non-A, non-B hepatitis may be demonstrated to be due to infection with the hepatitis C virus. With this assay, however, a prolonged interval between onset of disease and detection of antibody may occur. Until a more specific test for acute hepatitis C becomes available, these cases should be reported as non-A, non-B hepatitis. Chronic carriage or chronic hepatitis should not be reported.

These should be simple, objective, and discriminating (i.e. able to distinguish between people with disease and those without disease. For example,

• the presence of fever >101 o F or
• the presence of elevated titers of IgM anti-HAV or
• three or more loose bowel movements per day or muscle aches severe enough to limit the patient's activities

Also, case definitions should not include risk factors that you may want to evaluate, since all of the cases would have the risk factor, and this would be misleading. A case definition is not the same as a clinical diagnosis. Case definitions are an aid to conducting an epidemiologic investigation, whereas a clinical diagnosis is used to make treatment decisions for individual patients.

Sometimes investigators will use a loose definition early on to help them identity the extent of the outbreak. However, once the investigation progresses to the stage of conducting analytic studies to test hypotheses, a more specific definition should be used in order to reduce misclassification which would bias the results.

• Confirmed cases: These are usually laboratory confirmed cases, e.g., persons who attended a school's teacher appreciation luncheon on September 6, 2010 who had Salmonella isolated from a stool culture. Confirmed cases are best, because they are the most definitive. For most infectious diseases there will be a considerable number of infected people who have only mild symptoms (mildly symptomatic) or no symptoms at all (subclinical cases), and correctly identifying them as cases will rely on laboratory testing.
• Probable cases: These usually have characteristic clinical features of the disease, but lack laboratory confirmation, e.g., persons with bloody diarrhea who attended a school's teacher appreciation luncheon on September 6, 2010, but without laboratory confirmation.
• Possible cases: These have some of the clinical features, e.g., abdominal cramps and diarrhea (at least three stools in a 24-hour period) who attended a school's teacher appreciation luncheon on September 6, 2010.

Once a case definition has been established, there should be a concerted effort to identify as many cases as possible in order to accurately establish the magnitude and scope of the outbreak. The cases that are reported to the state and local health departments may represent only a small fraction of the total cases for the outbreak. Therefore, in addition to cases identified via passive surveillance (i.e., cases that self-report or are reported to the state and local health department by physicians' offices, clinics, hospitals, and laboratories) it is often fruitful to conduct active surveillance by calling hospitals, laboratories, clinics, and physicians offices in order to identify potential cases that otherwise would have gone unreported. As cases are identified, it can also be useful to ask them if they know of others who are similarly affected, e.g., family members and acquaintances. Occasionally, investigators will try to identify cases by posting notices in the media. These serve the dual purpose of alerting the public about potential hazards and identifying possible cases that have already become ill. For more information on case finding see Case Finding and Line Listing: A Guide for Investigators .

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Content ©2016. All Rights Reserved. Date last modified: May 3, 2016. Wayne W. LaMorte, MD, PhD, MPH

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A New Comparison of Nested Case-Control and Case-Cohort Designs and Methods

Ryung s. kim.

Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Ave, Bronx, New York, 10461 USA

Associated Data

Existing literature comparing statistical properties of nested case-control and case-cohort methods have become insufficient for present day epidemiologists. The literature has not reconciled conflicting conclusions about the standard methods. Moreover, a comparison including newly developed methods, such as inverse probability weighting methods, is needed. Two analytical methods for nested case-control studies and six methods for case-cohort studies using proportional hazards regression model were summarized and their statistical properties were compared. The answer to which design and method is more powerful was more nuanced than what was previously reported. For both nested case-control and case-cohort designs, inverse probability weighting methods were more powerful than the standard methods. However, the difference became negligible when the proportion of failure events was very low (<1%) in the full cohort. The comparison between two designs depended on the censoring types and incidence proportion: with random censoring, nested case-control designs coupled with the inverse probability weighting method yielded the highest statistical power among all methods for both designs. With fixed censoring times, there was little difference in efficiency between two designs when inverse probability weighting methods were used; however, the standard case-cohort methods were more powerful than the conditional logistic method for nested case-control designs. As the proportion of failure events in the full cohort became smaller (<10%), nested case-control methods outperformed all case-cohort methods and the choice of analytic methods within each design became less important. When the predictor of interest was binary, the standard case-cohort methods were often more powerful than the conditional logistic method for nested case-control designs.

Introduction

Case-cohort and nested case-control designs are the most common approaches for reducing the costs of exposure assessment in prospective epidemiologic studies. Exposure data in these designs are obtained on a subset of the full cohort. Nested case-control designs (or equivalently, incidence density sampling designs) include all cases and a pre-specified number of controls randomly chosen from the risk set at each failure time [ 1 ]. Case-cohort designs include all cases and one randomly selected sub-cohort from the risk set at baseline [ 2 ].

A few studies, all published before the year 2000, compared the statistical properties of the two designs. Prentice [ 2 ] and Self & Prentice [ 3 ] reported that case-cohort designs coupled with their respective analysis methods yielded higher statistical efficiency than nested case-control designs coupled with conditional logistic approach proposed by Thomas [ 1 ]. Langholz & Thomas [ 4 ] later pointed out that these conclusions had not accounted for repeated sampling of same persons in nested case-control designs. In their own simulation studies, nested case-control designs coupled with conditional logistic method was more efficient than the case-cohort designs coupled with Self & Prentice method [ 3 ] when there was moderate random censoring or staggered entries. Barlow et al. [ 5 ] reported that Prentice [ 2 ]’s method was more efficient than Barlow [ 6 ] which in turn was more efficient than Self & Prentice [ 3 ]. They reported that all these methods were more efficient than nested case-control designs coupled with conditional logistic approach when estimating the relative risk with respect to a binary predictor. They, however, did not find meaningful difference for a continuous predictor.

These reports have become insufficient for present day practitioners. First, more efficient analytical methods including inverse probability weighting methods have been developed, and a comparison of the new methods is needed. Second, the literature has not reconciled the seemingly conflicting conclusions even about the traditional methods. Self & Prentice [ 3 ] concluded case-cohort designs coupled with their method is more efficient than the nested case-control designs coupled with conditional logistic method. On the contrary, Langholz & Thomas [ 4 ] concluded that conditional logistic method out-performed Self & Prentice [ 3 ] when there was moderate random censoring. By Barlow et al [ 5 ], the order is reversed yet again and, in fact, both were outperformed by Prentice [ 2 ]. All these studies implied there should be a single answer to what is the best design and analysis method, considered one non-zero value of log relative risk, one cohort size, and a binary predictor. The real answer may be more nuanced. A more comprehensive investigation with varying magnitude of relative risks, cohort sizes, and incidence proportion may sort out what affects the relative performance. In addition, the relative performance is unknown for continuous predictors for which conditional logistic approach suffers less from sparse samples. Third, the literature compared efficiency of the methods but not power. However, a seemingly large difference in efficiency may not yield practically meaningful difference in power. For example, when the true relative risk is large, a large difference in efficiency may lead to only a moderate difference in power because the power will reach near the upper limit of one. In the author’s opinion, what has happed in practice is that researchers would choose one of the designs without a clear understanding about the ramification of the choice on statistical power.

This article first summarizes various analytical methods for nested case-control and case-cohort designs using Cox proportional hazards model. We perform simulation studies to compare bias, efficiencies, type 1 errors, and powers of the methods by varying the following design factors: the type of predictors (continuous or binary), the magnitude of hazard ratio, cohort size, the number of controls, censoring type, and the proportion of failure events. Two analytical methods for nested case-control studies are considered: conditional logistic approach of Thomas [ 1 ] and the inverse inclusion probability method of Samuelsen [ 7 ] coupled with an approximate jackknife standard error [ 8 , 9 ]. Six methods for case-cohort studies are considered: Prentice [ 2 ], Self & Prentice [ 3 ], Lin & Ying [ 10 ], Barlow [ 6 ], and both Prentice [ 2 ] and Binder [ 11 ] coupled with approximate jackknife standard errors.

Notations and Methods

Consider a cohort study with N subjects. Subject i enters the study at a fixed time a i . The subject has the failure time T i and the censoring time W i . The investigator observes only Y i = min( T i , W i ). The failure time and censoring time are assumed to be independent. X i ( t ) is a time dependent covariate vector of the subject. Assume that the hazard function λ i ( t ) of the failure time follows the model λ i ( t ) = λ 0 ( t ) exp( X i ( t )β) where λ 0 ( t ) is an unspecified baseline hazard function and β is the parameter vector of interest. Then, inferences are typically made by maximizing Cox partial likelihood:

δ i is one if subject i failed during the study, otherwise it is zero; R i ={ j: Y j ≥ Y i > a j } is a risk set, an index set of subjects at risk at the failure time of subject i .

In nested case-control studies, for each case, m controls are sampled without replacement at each Y i where δ i =1 from R i ∩{ i } c , i.e. from the subjects still at risk at the time of the failure of the case [ 1 ]. Notice that the controls may include both failures and non-failures. Case-cohort studies include all cases and a randomly selected sub-cohort from the risk set at baseline [ 2 ], i.e., controls are randomly selected once from R 0 , the risk set at baseline. Let C i denote the set of controls selected from R i and C denote the union of all controls. For case-cohort design, C = C 0 is the subcohort. For nested case-control designs, C =∪ i:δ i =1 C i . Then S ={ i: δ i =1}∪ C is the index set of subjects that were ever included in the sample. R i ∩ S is a risk set in the sample, an index set of subjects included in the sample who are also at risk at failure time of subject i . By changing the weighting strategies, the following pseudo/partial-likelihood was maximized by Thomas [ 1 ] and Samuelsen [ 7 ] for nested case-control designs, by Prentice [ 2 ], Self & Prentice [ 3 ], and Barlow [ 6 ] for case-cohort designs, by Binder [ 11 ] for complex survey data, and by Lin & Ying [ 10 ] for incomplete data:

The top section of Table 1 shows how the methods use different weights in the pseudo/partial-likelihood ( 2 ). Barlow [ 5 ] explained the weights in the first three methods (from the top). Unlike these methods, the inverse probability weighting methods, Binder [ 11 ] and Samuelsen [ 7 ], include the non-subcohort case in earlier risk sets and use knowledge about the future case status of that individual. Barlow [ 5 ] speculated that such use might bias the estimates in case-cohort designs but Binder [ 11 ] and Lin [ 12 ] proved the consistency of the estimator for complex sampling designs. Samuelsen [ 7 ] proved the consistency for nested case-control designs. The same argument of the proofs can be applied to case-cohort designs. In short, this is because the pseudo-likelihood ( 2 ) is a design-consistent estimator of Cox’s partial likelihood ( 1 ) conditional on the full cohort and considering only the randomness of the indicators of which subjects are to be included in the particular case-cohort study. This property ensures that inverse probability weighted estimator to be a design-consistent estimator of the Cox’s estimator, which in turn is a model-consistent estimator of β under the proportional hazards assumption. We note that ( 2 ) for the case of Thomas [ 1 ] is a partial likelihood, and not a pseudo-likelihood, since its contributions are score unbiased and the variance of the score is the expected information.

Denominator Weights in the Pseudo/Partial-likelihood and Variance Estimators

In the top section, the denominator weights in the pseudo-likelihood for Prentice (1986), Self & Prentice (1988), and Barlow (1994) are reported by Barlow et al (1999). Binder (1992) and Samuelsen (1997) are inverse probability weighting (IPW) methods. C is the union of all controls. p j is the probability of j th subject to be included in a nested case-control sample and π is the subcohort sampling proportion for case-cohort designs.

In case-cohort studies, the proportion of sub-cohort is fixed at, say, π. For nested case-control studies, Samuelsen [ 7 ] calculated inclusion probabilities and Kim [ 8 ] extended them to account for ties and additional matching. The inclusion probability of subject i is the following:

Let H i be the index set of the subjects with the same values of matching variables as subject i. k ji is the size of R j ∩ H i or the number of subjects at risk at t j with the same values of matching variables as subject i; b ji is the number of subjects in H i that failed exactly at t j ; m is the number of controls per each failure.

The weights in the top section of Table 1 give insight into Barlow [ 5 ]’s finding of the higher efficiency of Prentice [ 2 ] over Self & Prentice [ 3 ]’s method which uses less data to estimate the covariate contribution, and Barlow [ 6 ]’s method which always uses equal or greater weights. It is reasonable to hypothesize that inverse probability weighting methods would have higher efficiencies than others in both designs because they use the non-subcohort cases in earlier risk sets. It has been shown that such was the case for the nested case-control designs [ 7 , 9 ] but not yet for the case-cohort designs.

The stated assumption that failure and censoring being independent was in fact more than necessary. The appropriate conditions are that the form of the intensity (or the rate ratio) does not change due to censoring or sampling. See conditions for full cohort in Anderson and Gill [ 13 ], for case-cohort in Self and Prentice [ 3 ], and for nested case-control in Borgan et al [ 14 ].

Standard Error Estimation

We studied if various standard error estimators meaningfully affect the performance of the aforementioned methods. Prentice [ 2 ] and Self & Prentice [ 3 ] each proposed asymptotic variance estimators for their respective methods. Lin and Ying [ 10 ]’s estimating equation for incomplete data reduces to the pseudo-likelihood score function of the Self & Prentice [ 3 ] for case-cohort designs. Therefore, Lin and Ying [ 10 ]’s proposed approximate jackknife variance estimator is an alternative variance estimator for Self & Prentice’s method [ 3 ]. Barlow [ 6 ] also proposed an approximate jackknife variance estimator for his method. Binder [ 11 ] originally provided a variance estimator that accounts only for the sampling variation from a finite cohort but Lin [ 12 ] later provided the variance estimator for Binder’s method accounting for the sampling of the cohort from an infinite super-population.

For nested case-control designs, Goldstein & Langholz [ 4 ] proved that the typical standard errors from standard conditional logistic software are valid for the conditional logistic approach of Thomas [ 1 ]. Samuelsen [ 7 ]’s proposed an asymptotic variance estimator for the inverse probability weighting method that is similar to the variance estimator of Lin [ 12 ].

The second section of Table 1 summarizes the various standard errors. Therneau [ 15 ] pointed out that Self & Prentice [ 3 ] variance converges to the usual Cox model variance as the sample size increases to the size of the full cohort. This is also true for Lin [ 12 ], Thomas [ 1 ], and Samuelsen [ 7 ]. On the other hand, the Lin & Ying [ 10 ] estimate converges to the approximate jackknife estimate of Lin & Wei [ 16 ]. These approximate jackknife type standard errors have an advantage that they are available in standard software such as SAS and R without any extra programming. We did not calculate Lin [ 12 ] and Samuelsen [ 7 ]’s variance estimators for inverse probability weighting methods. They both require computational memory in the order of O( n 2 ) to compute all pair-wise co-inclusion probabilities. Instead, we used approximate jackknife estimators. Kim [ 8 , 9 ] showed that they accurately estimated the empirical variance and the estimates were remarkably close to that of Samuelsen [ 7 ]. We also did not calculate the variance proposed by Prentice [ 2 ] and used the form of variance estimator proposed by the Self & Prentice [ 3 ] as well as an approximate jackknife estimator.

Programming

All analyses were programmed in R environment [ 17 ]. We followed Therneau and Li [ 15 ]’s guidance in programming Self & Prentice [ 3 ] and Lin & Ying [ 10 ]. And we followed Barlow [ 5 ]’s guidance in programming Prentice [ 2 ] and Barlow [ 6 ]. Inverse probability weighting methods and approximate jackknife type variance estimators are straightforward to program in R using weights and cluster options in coxph function. See reference [ 18 ] for the R code.

Exponential failure times T with rate exp( β 1 X 1 + β 2 X 2 ) were generated for full cohorts with size N = 500, 1,000, or 1,500. In addition, X 1 was assumed to be distributed as a standard normal variable, and X 2 was specified as independent Bernoulli variables with success probability of (1+exp(− X 1 )) −1 . The distribution of covariates was set up so that a mild multicollinearity existed. The true log hazard ratio β 1 assumed the values of 0, 0.1, 0.2… 0.8. The hazard ratios, therefore, ranged between 1 and 24.5 by an increase of the variable equivalent to four standard deviations. The log hazard ratio for X 2 was set as β 2 =0.5. Censoring times were uniformly distributed between 0 and c , the upper limit of censoring, which was chosen so that the proportion of failure events was, on average, 15% in the full cohort. For each subject, either the failure or censoring time was observed, whichever occurred earlier. The log hazard ratios and their standard errors in the full cohort were estimated under the Cox proportional hazards model.

Nested case-control samples were than selected with varying numbers of controls, m = 1, 2, or 5, at each failure time. When each nested case-control sample was selected, a case-cohort sample was also selected. To make the average sample size of the two designs the same, the sampling proportion for the subcohort of the case-cohort sample was set as the number of non-failures in the nested case-control sample divided by the number of non-failures in the full cohort. For simplicity, additional matching factors were not used.

For each simulated nested case-control and case-cohort data set, log hazard ratios were estimated according to the pseudo-likelihood ( 2 ) using weights defined in Table 1 along with the standard errors methods in the table. This overall process including the generation of the full cohort, nested case-control sample, and case-cohort sample was repeated 5,000 times. For the estimation of empirical type 1 error (i.e. when β 1 =0), the overall process was repeated 20,000 times.

Figure 1 shows the empirical biases in estimating β 1 from the full cohort analysis, two nested case-control methods, and four case-cohort methods. When sample sizes were small to moderate ( N = 500, m = 1 , or N = 500, m=2, or N = 1,000, m = 1), Self & Prentice [ 3 ] and Barlow [ 6 ]’s methods over-estimated non-zero β 1 about 5–20%. The biases of other methods were less than 5% of β 1 except for the smallest sample sizes considered ( m =1, N =500) when the average sample size ( n *) was 131.9. The biases became negligible as the sample size increased.

The considered methods are the full cohort analysis, two nested case-control (NCC) methods, which are the conditional logistic approach by Thomas (1977), and the inverse probability weighting method by Samuelsen (1997), and four case-cohort (CCH) methods, which are the inverse probability weighting method by Binder (1992), and the methods by Prentice (1986), Self & Prentice (1988), and Barlow (1994). The average sample size n * and the average subcohort proportion π* are shown in the titles. Only the results for N =500, 1,000 are shown. See Web Figure 4 for the result when N =1,500.

Figure 2 shows the empirical standard errors by the methods. Consistent with the report by Barlow et al [ 5 ], we observed higher efficiency of Prentice [ 2 ] over the methods of Self & Prentice [ 3 ] and Barlow [ 6 ]. Notably, inverse probability weighting methods yielded higher efficiency compared to other methods in both case-cohort and nested case-control designs. This is because they use more data, namely the non-subcohort cases in earlier risk sets, to estimate the covariate contribution in ( 2 ). As we expected, nested case-control designs showed higher efficiency over case-cohort when inverse probability weighting methods are used in both designs. Interestingly, contrary to Barlow et al [ 5 ]’s report, the conditional logistic approach of Thomas [ 1 ] outperformed Prentice [ 2 ], Self & Prentice [ 3 ], and Barlow [ 6 ]. The discrepancy between the findings comes from X 1 being a continuous predictor for which conditional logistic approach suffers less from the sparse samples with small numbers of discordant pairs. Barlow et al. [ 5 ] had reported that these methods were more efficient than the conditional logistic approach when estimating a relative risk with respect to a binary predictor. The figure also affirmed the theoretical finding by Zhang and Goldstein [ 19 ] that for Self-Prentice [ 3 ] to obtain greater than 80% optimal efficiency at β =0, the sampling fraction needs to be at least as three to five times the proportion of failure events.

The empirical standard errors of β 1 estimators are shown for the full cohort analysis, two nested case-control (NCC) methods, which are the conditional logistic approach by Thomas (1977) and the inverse probability weighting method by Samuelsen (1997), and four case-cohort (CCH) methods, which are the inverse probability weighting method by Binder (1992), and the methods by Prentice (1986), Self & Prentice (1988), and Barlow (1994). The average sample size n * and the average subcohort proportion π* are shown in the titles. Only the results for N =500, 1,000 are shown. See Web Figure 4 for the result when N =1,500.

Controlling the nominal type 1 error rate at 0.05 in testing H 0 : β 1 =0, the empirical power and type 1 error rates were measured. All methods yielded empirical type 1 error rates close to the nominal rate ( Table 2 ) with the exception of the inverse probability weighting methods and Prentice [ 2 ] that were mildly inflated when the sample sizes were small (<0.06; N =500, m =1 or N =1,000, m =1). Figure 3 shows the empirical power of the methods. The conclusions are similar to that from the empirical standard errors. Nested case-control designs coupled with the inverse probability weighting method by Samuelsen [ 7 ] was most powerful. Also among the case-cohort methods, inverse probability method by Binder [ 11 ] was most powerful, and then it was Prentice [ 2 ] over the methods of Barlow [ 6 ] and Self & Prentice [ 3 ]. The first column of the Table 3 demonstrates the power of the methods when N =500, m =2, and β 1 =0.5. For example, the empirical powers by Samuelsen [ 7 ], Binder [ 11 ], Thomas [ 1 ], Prentice [ 2 ], Barlow [ 6 ], Self-Prentice [ 3 ] were 0.90, 0.85, 0.85, 0.83, 0.83, and 0.80. Notice that the empirical variances of Binder, Thomas, Prentice, Barlow, and Self-Prentice were 22%, 23%, 47%, 80%, and 91% greater than that of Samuelsen in the same setting. The relative difference of power was moderate even when the difference of variance seemed dramatic.

The nominal type 1 error rate was 0.05. The empirical power of nine methods is measured: full cohort analysis, the conditional logistic approach by Thomas (1997), inverse probability weighting methods by Samuelsen (1997) coupled with approximate jackknife (AJK) variance estimator (Kim 2013a), the inverse probability weighting methods by Binder (1992) coupled with AJK variance estimator, Prentice (1986), Prentice (1986) coupled with AJK variance estimator, Self & Prentice (1988), Self & Prentice coupled with AJK variance estimator (i.e. Lin & Ying 1993), and Barlow (1993). The average sample size n * and the average subcohort proportion π* are shown in the titles. Only the results for N =500, 1,000 are shown. CCH and NCC are abbreviations for case-cohort and nested case-control designs, respectively. See Web Figure 4 for the result when N =1,500.

Empirical Type 1 Error Testing H 0 : β 1 =0

The rows from the top to bottom are type 1 errors by full cohort analysis, conditional logistics approach of Thomas (1977) for nested case-control (NCC) designs, inverse probability weighting methods (IPW) by Samuelsen (1997) coupled with approximate jackknife (AJK) variance estimator, IPW by Binder (1992) coupled with AJK variance estimator for case-cohort (CCH) designs, Prentice (1986), Prentice (1986) coupled with AJK variance estimator, Self & Prentice (1988), Self & Prentice (1988) coupled with AJK variance estimator (i.e. Lin & Ying 1993), and Barlow (1994). CCH and NCC are abbreviations for case-cohort and nested case-control designs, respectively.

Empirical Power for m =2

The methods from the top to bottom are: full cohort analysis, conditional logistics approach of Thomas (1977) for nested case-control (NCC) designs, inverse probability weighting methods (IPW) by Samuelsen (1997) coupled with approximate jackknife (AJK) variance estimator, IPW by Binder (1992) coupled with AJK variance estimator for case-cohort (CCH) designs, Prentice (1986), Prentice (1986) coupled with AJK variance estimator, Self & Prentice (1988), Self & Prentice (1988) coupled with AJK variance estimator (i.e. Lin & Ying 1993), and Barlow (1994). CCH and NCC are abbreviations for case-cohort and nested case-control designs, respectively.

Next, to study the relative performance for binary predictors, we repeated the simulation study but this time for β 2 , the log hazard ratio with respect to the binary predictor X 2 . The β 2 assumed the values of 0, 0.2, 0.4… 2.0. The log hazard ratio for X 1 was set as β 1 =0.5. Again, empirical biases ( Web Figure 1 ) were less than 5% of β 2 for all methods except for the smallest sample sizes considered ( m =1, N =500). Inverse probability weighting methods yielded the highest efficiency in both case-cohort and nested case-control designs ( Web Figure 2 ). We observed higher efficiency of Prentice [ 2 ] over the methods of Self & Prentice [ 3 ] and Barlow [ 6 ]. And nested case-control designs yielded higher efficiency over case-cohort when inverse probability weighting methods were used in both designs. In short, some conclusions from the analysis of β 1 were confirmed in the analysis β 2 .

However, the conditional logistic approach of Thomas [ 1 ] was less stable for the binary predictor when the sample sizes were small ( N =500 , m =1 or N =1,000 , m =1; Web Figure 2 ). There were a number of sparse samples in which hazard ratios were inestimable by the conditional logistic approach and, with less frequency, Self & Prentice [ 3 ]. Such sparse samples were more frequent with large β 2 , which makes in unlikely for a subject with X 2 =1 to fail. For example, when N =500, m =1, β 2 =2, 4% of the samples did not have any risk set that had both at least one case with X 2 =0 and at least one control with X 2 = 1. The relative risk estimates by the conditional logistic approach in these samples were infinity. For fair comparison, these sparse samples were excluded from the analysis by all considered methods. Notice that the differences in power between Thomas [ 1 ], Prentice [ 2 ], Barlow [ 6 ], and Self-Prentice [ 3 ] were still moderate ( Web Figure 3 ).

To study how incidence proportion affects the relative performance, we then repeated the simulation study this time with varying proportion of failure events in the full cohort. Here the upper limit of random censoring was varied so that the proportion of failure events in the full cohorts was, on average, 0.1%, 1%, 5%, or 10%. The sizes of the full cohort were adjusted to contain the same average number of cases as the above simulation studies. For example, when the proportion of failure events was set at 1%, the cohort size was N = 7,500, 15,000, or 22,500. The β 1 assumed the values of 0, 0.1, 0.2… 0.8. The log hazard ratio for X 2 was set as β 2 =0.5. In testing H 0 : β 1 =0, both nested case-control methods were more powerful than any case-cohort method when the proportion of failure events was less than or equal to 10% and the difference in power grew greater as the proportion became smaller. Interestingly, in both designs, the difference in power between inverse probability weighting method and the standard methods (Prentice [ 2 ] for case-cohort studies and the conditional logistic method for the nested case-control studies) became ignorable as the proportion of failure events became very low (≤ 1%; Table 3 shows when m =2, β 1 =0.5). This is because the inverse probability weights for the controls become too large compared to the weights for the cases when the proportion of failure events is low. There seems to be a balancing effect on efficiency: inverse probability weighting methods gain efficiency by using more controls in the risk sets but lose it when variation among the weights is large.

We also suspected that the random censoring might favor nested case-control design as case-cohort design was intended for the situation where most of the censoring was administrative at the end so that controls would serve in many risk sets. Intuitively, nested case-control methods gain power by over-sampling from controls with longer follow-ups but such gain would be lost when censoring and entry times are the same across controls. In order to explore the effect of censoring type, we repeated the simulation study this time with fixed censoring times, which were chosen so that the proportion of failure events was 15% in the full cohort. The β 1 assumed the values of 0, 0.1, 0.2… 0.8. The log hazard ratio for X 2 was set as β 2 =0.5. While the standard case-cohort methods, Prentice [ 2 ], Self-Prentice [ 3 ], and Barlow [ 6 ], were all more powerful than the conditional logistic method for nested case-control designs across different values of β 1 , the inverse probability weighting methods were still more efficient than other methods within each design ( Table 3 ; Only when N =500 , m =2, β 1 =0.5 is shown). Interestingly, there was little difference in efficiency between two designs when inverse probability weighting methods were used.

For both designs, inverse probability weighting methods were more powerful than the standard methods. This is because they use more data, namely the non-subcohort cases in earlier risk sets, to estimate the covariate contribution in the pseudo-likelihood. However, the difference became negligible when the proportion of failure events was very low (<1%).

The comparison between two designs depended on the censoring types and incidence proportion. With random censoring, nested case-control designs coupled with the inverse probability weighting method proposed by Samuelsen [ 7 ] showed the highest statistical power among all methods for both designs. With fixed censoring times, there was little difference in efficiency between two designs when inverse probability weighting methods were used, however, the standard case-cohort methods, Prentice [ 2 ], Self-Prentice [ 3 ], and Barlow [ 6 ], were often more powerful than the conditional logistic method for nested case-control designs. As the proportion of failure events became smaller (<10%), both nested case-control methods outperformed all case-cohort methods and the choice of analytic methods within each type of design became less important. When the predictor was binary, again, the standard case-cohort were often more powerful than the conditional logistic method for nested case-control designs.

This explains the discrepancy between the reports by Langholz & Thomas [ 4 ] and Barlow et al [ 5 ]: the former report was based on random censoring and the latter report was based on type 2 censoring. It shows that the answer to which design and method is more efficient is more nuanced than what was previously reported. In addition to what we investigated, the relative performance may also depend on the type of left truncation, and the degree of stratification.

Furthermore, statistical power is not the sole determinant of choosing study designs or analytical methods. For example, the inverse probability methods require the retrospective access to the outcome and the matching variables of the full cohort in order to compute inclusion probabilities. Moreover, there are model spaces under which certain designs and analyses are invalid. In particular, the inverse probability weighting methods are invalid when the cohort is “finely stratified” (i.e., the number of strata increases with sample size) since the methods require the consistency of the weights. Goldstein and Zhang [ 20 ] proved that when highly stratified cohorts are followed over a short period, conditional logistic approach achieves optimal efficiency under the stratified proportional hazards model. In other cases, case-cohort designs has been preferred for the ease in designing and analyzing a follow-up study with respect to new secondary outcomes [ 21 ].

As the new analytical methods are being developed, the conclusion about the relative performance may still change. For example, Chen [ 22 , 23 ] improved inverse probability weighting methods for case-cohort and nested case-control designs by refining weights by averaging the observed covariates from subjects with similar failure times to estimate contribution from unselected controls. The relative performance would depend on the correlation between failure times and covariates for local averaging. In addition, there have been developments to non-parametrically model predictors of interest conditioned on other available covariates. In some important situations, these maximum semiparametric likelihood has shown to increase the efficiency [ 24 , 25 ].

Left truncation, or delayed entries, must be accounted in the pseudo/partial likelihoods to avoid bias in estimating hazard ratios under proportional hazards model. When truncation and failure times are independent, the full cohort likelihoods can be adjusted by excluding subjects from the risk sets corresponding to the times before their enrollment. In nested case-control studies, controls are selected only from those at risk that are already enrolled in the studies. Small sample properties of the case-cohort and the nested case-control methods under varying degrees of left-truncation have not been reported yet.

Staggered entries, like random right censorings, may favor nested case-control methods over case-cohort methods because the former gain power by over-sampling from controls with longer follow-ups especially when the incidence proportion is not very small.

For recurrent events, proportional intensity models have been proposed based on total time of follow-up [ 13 , 26 ] or gap time [ 26 ] while accounting for dependency among the repeated measurements with a marginal ‘working independence’ variance. An alternate approach is to model dependency by random effects. A modified nested case-control sampling strategy for recurrent events were proposed by Lubin [ 27 ], along with the usual conditional logistic likelihood, as an extension of recurrent events method by Prentice et al [ 26 ]. In case-cohort studies, Zhang et al [ 28 ] extended Andersen and Gill’s model [ 13 ] using the inverse probability weighting method and Chen & Chen [ 29 ] modeled the impact of earlier events on the subsequent events using Prentice’s approach for case-cohort studies [ 2 ].

The proportional hazards assumption can have substantial importance [ 30 ]. For example, the effects on breast cancer metastases of both higher tumor grades and negative hormone receptor diminished over time [ 30 , 31 ]. Recently, methods have been developed to assess proportional hazards assumption in case-cohort and nested case-control studies. For example, correlation tests between Schoenfeld residuals and event time were extended to case-cohort studies [ 30 ] and a goodness-of-fit test based on inverse probability weighting method was developed for nested case-control studies [ 32 ]. Sometimes, the violation of proportional hazards assumption can be remedied through time-invariance predictors. While it is out of scope of this paper, we suspect the reported relative performances may differ with time-varying predictors.

Informative censoring can cause bias when, for example, those who do well drop out from treatment group and those who do worse drop out from control group [ 33 ]. In full cohort studies, informative censoring has been modeled explicitly, for example, via the relationship of hazard functions [ 34 ] or survival functions [ 35 ] between censored and uncensored subjects in proportional hazards regression models. Some used data collected after censoring to address the issue [ 36 ]. These methods have not been extended to case-cohort or nested case-control study designs.

Supplementary Material

10654_2014_9974_moesm1_esm, 10654_2014_9974_moesm2_esm, 10654_2014_9974_moesm3_esm, 10654_2014_9974_moesm4_esm, acknowledgments.

This work was supported by the National Institutes of Health Grants 1UL1RR025750-01, P30 CA01330-35; and the National Research Foundation of Korea Grant NRF-2012-. The author is deeply thankful for the constructive comments from the anonymous referees, which led to significant improvement of this work.

Conflict of Interest

None declared.