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  • What Is a Case-Control Study? | Definition & Examples

What Is a Case-Control Study? | Definition & Examples

Published on February 4, 2023 by Tegan George . Revised on June 22, 2023.

A case-control study is an experimental design that compares a group of participants possessing a condition of interest to a very similar group lacking that condition. Here, the participants possessing the attribute of study, such as a disease, are called the “case,” and those without it are the “control.”

It’s important to remember that the case group is chosen because they already possess the attribute of interest. The point of the control group is to facilitate investigation, e.g., studying whether the case group systematically exhibits that attribute more than the control group does.

Table of contents

When to use a case-control study, examples of case-control studies, advantages and disadvantages of case-control studies, other interesting articles, frequently asked questions.

Case-control studies are a type of observational study often used in fields like medical research, environmental health, or epidemiology. While most observational studies are qualitative in nature, case-control studies can also be quantitative , and they often are in healthcare settings. Case-control studies can be used for both exploratory and explanatory research , and they are a good choice for studying research topics like disease exposure and health outcomes.

A case-control study may be a good fit for your research if it meets the following criteria.

  • Data on exposure (e.g., to a chemical or a pesticide) are difficult to obtain or expensive.
  • The disease associated with the exposure you’re studying has a long incubation period or is rare or under-studied (e.g., AIDS in the early 1980s).
  • The population you are studying is difficult to contact for follow-up questions (e.g., asylum seekers).

Retrospective cohort studies use existing secondary research data, such as medical records or databases, to identify a group of people with a common exposure or risk factor and to observe their outcomes over time. Case-control studies conduct primary research , comparing a group of participants possessing a condition of interest to a very similar group lacking that condition in real time.

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See an example

another name for case control study

Case-control studies are common in fields like epidemiology, healthcare, and psychology.

You would then collect data on your participants’ exposure to contaminated drinking water, focusing on variables such as the source of said water and the duration of exposure, for both groups. You could then compare the two to determine if there is a relationship between drinking water contamination and the risk of developing a gastrointestinal illness. Example: Healthcare case-control study You are interested in the relationship between the dietary intake of a particular vitamin (e.g., vitamin D) and the risk of developing osteoporosis later in life. Here, the case group would be individuals who have been diagnosed with osteoporosis, while the control group would be individuals without osteoporosis.

You would then collect information on dietary intake of vitamin D for both the cases and controls and compare the two groups to determine if there is a relationship between vitamin D intake and the risk of developing osteoporosis. Example: Psychology case-control study You are studying the relationship between early-childhood stress and the likelihood of later developing post-traumatic stress disorder (PTSD). Here, the case group would be individuals who have been diagnosed with PTSD, while the control group would be individuals without PTSD.

Case-control studies are a solid research method choice, but they come with distinct advantages and disadvantages.

Advantages of case-control studies

  • Case-control studies are a great choice if you have any ethical considerations about your participants that could preclude you from using a traditional experimental design .
  • Case-control studies are time efficient and fairly inexpensive to conduct because they require fewer subjects than other research methods .
  • If there were multiple exposures leading to a single outcome, case-control studies can incorporate that. As such, they truly shine when used to study rare outcomes or outbreaks of a particular disease .

Disadvantages of case-control studies

  • Case-control studies, similarly to observational studies, run a high risk of research biases . They are particularly susceptible to observer bias , recall bias , and interviewer bias.
  • In the case of very rare exposures of the outcome studied, attempting to conduct a case-control study can be very time consuming and inefficient .
  • Case-control studies in general have low internal validity  and are not always credible.

Case-control studies by design focus on one singular outcome. This makes them very rigid and not generalizable , as no extrapolation can be made about other outcomes like risk recurrence or future exposure threat. This leads to less satisfying results than other methodological choices.

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.

  • Student’s  t -distribution
  • Normal distribution
  • Null and Alternative Hypotheses
  • Chi square tests
  • Confidence interval
  • Quartiles & Quantiles
  • Cluster sampling
  • Stratified sampling
  • Data cleansing
  • Reproducibility vs Replicability
  • Peer review
  • Prospective cohort study

Research bias

  • Implicit bias
  • Cognitive bias
  • Placebo effect
  • Hawthorne effect
  • Hindsight bias
  • Affect heuristic
  • Social desirability bias

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A case-control study differs from a cohort study because cohort studies are more longitudinal in nature and do not necessarily require a control group .

While one may be added if the investigator so chooses, members of the cohort are primarily selected because of a shared characteristic among them. In particular, retrospective cohort studies are designed to follow a group of people with a common exposure or risk factor over time and observe their outcomes.

Case-control studies, in contrast, require both a case group and a control group, as suggested by their name, and usually are used to identify risk factors for a disease by comparing cases and controls.

A case-control study differs from a cross-sectional study because case-control studies are naturally retrospective in nature, looking backward in time to identify exposures that may have occurred before the development of the disease.

On the other hand, cross-sectional studies collect data on a population at a single point in time. The goal here is to describe the characteristics of the population, such as their age, gender identity, or health status, and understand the distribution and relationships of these characteristics.

Cases and controls are selected for a case-control study based on their inherent characteristics. Participants already possessing the condition of interest form the “case,” while those without form the “control.”

Keep in mind that by definition the case group is chosen because they already possess the attribute of interest. The point of the control group is to facilitate investigation, e.g., studying whether the case group systematically exhibits that attribute more than the control group does.

The strength of the association between an exposure and a disease in a case-control study can be measured using a few different statistical measures , such as odds ratios (ORs) and relative risk (RR).

No, case-control studies cannot establish causality as a standalone measure.

As observational studies , they can suggest associations between an exposure and a disease, but they cannot prove without a doubt that the exposure causes the disease. In particular, issues arising from timing, research biases like recall bias , and the selection of variables lead to low internal validity and the inability to determine causality.

Sources in this article

We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.

George, T. (2023, June 22). What Is a Case-Control Study? | Definition & Examples. Scribbr. Retrieved February 22, 2024, from https://www.scribbr.com/methodology/case-control-study/
Schlesselman, J. J. (1982). Case-Control Studies: Design, Conduct, Analysis (Monographs in Epidemiology and Biostatistics, 2) (Illustrated). Oxford University Press.

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What Is A Case Control Study?

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A case-control study is a research method where two groups of people are compared – those with the condition (cases) and those without (controls). By looking at their past, researchers try to identify what factors might have contributed to the condition in the ‘case’ group.

Explanation

A case-control study looks at people who already have a certain condition (cases) and people who don’t (controls). By comparing these two groups, researchers try to figure out what might have caused the condition. They look into the past to find clues, like habits or experiences, that are different between the two groups.

The “cases” are the individuals with the disease or condition under study, and the “controls” are similar individuals without the disease or condition of interest.

The controls should have similar characteristics (i.e., age, sex, demographic, health status) to the cases to mitigate the effects of confounding variables .

Case-control studies identify any associations between an exposure and an outcome and help researchers form hypotheses about a particular population.

Researchers will first identify the two groups, and then look back in time to investigate which subjects in each group were exposed to the condition.

If the exposure is found more commonly in the cases than the controls, the researcher can hypothesize that the exposure may be linked to the outcome of interest.

Case Control Study

Figure: Schematic diagram of case-control study design. Kenneth F. Schulz and David A. Grimes (2002) Case-control studies: research in reverse . The Lancet Volume 359, Issue 9304, 431 – 434

Quick, inexpensive, and simple

Because these studies use already existing data and do not require any follow-up with subjects, they tend to be quicker and cheaper than other types of research. Case-control studies also do not require large sample sizes.

Beneficial for studying rare diseases

Researchers in case-control studies start with a population of people known to have the target disease instead of following a population and waiting to see who develops it. This enables researchers to identify current cases and enroll a sufficient number of patients with a particular rare disease.

Useful for preliminary research

Case-control studies are beneficial for an initial investigation of a suspected risk factor for a condition. The information obtained from cross-sectional studies then enables researchers to conduct further data analyses to explore any relationships in more depth.

Limitations

Subject to recall bias.

Participants might be unable to remember when they were exposed or omit other details that are important for the study. In addition, those with the outcome are more likely to recall and report exposures more clearly than those without the outcome.

Difficulty finding a suitable control group

It is important that the case group and the control group have almost the same characteristics, such as age, gender, demographics, and health status.

Forming an accurate control group can be challenging, so sometimes researchers enroll multiple control groups to bolster the strength of the case-control study.

Do not demonstrate causation

Case-control studies may prove an association between exposures and outcomes, but they can not demonstrate causation.

A case-control study is an observational study where researchers analyzed two groups of people (cases and controls) to look at factors associated with particular diseases or outcomes.

Below are some examples of case-control studies:
  • Investigating the impact of exposure to daylight on the health of office workers (Boubekri et al., 2014).
  • Comparing serum vitamin D levels in individuals who experience migraine headaches with their matched controls (Togha et al., 2018).
  • Analyzing correlations between parental smoking and childhood asthma (Strachan and Cook, 1998).
  • Studying the relationship between elevated concentrations of homocysteine and an increased risk of vascular diseases (Ford et al., 2002).
  • Assessing the magnitude of the association between Helicobacter pylori and the incidence of gastric cancer (Helicobacter and Cancer Collaborative Group, 2001).
  • Evaluating the association between breast cancer risk and saturated fat intake in postmenopausal women (Howe et al., 1990).

Frequently asked questions

1. what’s the difference between a case-control study and a cross-sectional study.

Case-control studies are different from cross-sectional studies in that case-control studies compare groups retrospectively while cross-sectional studies analyze information about a population at a specific point in time.

In  cross-sectional studies , researchers are simply examining a group of participants and depicting what already exists in the population.

2. What’s the difference between a case-control study and a longitudinal study?

Case-control studies compare groups retrospectively, while longitudinal studies can compare groups either retrospectively or prospectively.

In a  longitudinal study , researchers monitor a population over an extended period of time, and they can be used to study developmental shifts and understand how certain things change as we age.

In addition, case-control studies look at a single subject or a single case, whereas longitudinal studies can be conducted on a large group of subjects.

3. What’s the difference between a case-control study and a retrospective cohort study?

Case-control studies are retrospective as researchers begin with an outcome and trace backward to investigate exposure; however, they differ from retrospective cohort studies.

In a  retrospective cohort study , researchers examine a group before any of the subjects have developed the disease, then examine any factors that differed between the individuals who developed the condition and those who did not.

Thus, the outcome is measured after exposure in retrospective cohort studies, whereas the outcome is measured before the exposure in case-control studies.

Boubekri, M., Cheung, I., Reid, K., Wang, C., & Zee, P. (2014). Impact of windows and daylight exposure on overall health and sleep quality of office workers: a case-control pilot study. Journal of Clinical Sleep Medicine: JCSM: Official Publication of the American Academy of Sleep Medicine, 10 (6), 603-611.

Ford, E. S., Smith, S. J., Stroup, D. F., Steinberg, K. K., Mueller, P. W., & Thacker, S. B. (2002). Homocyst (e) ine and cardiovascular disease: a systematic review of the evidence with special emphasis on case-control studies and nested case-control studies. International journal of epidemiology, 31 (1), 59-70.

Helicobacter and Cancer Collaborative Group. (2001). Gastric cancer and Helicobacter pylori: a combined analysis of 12 case control studies nested within prospective cohorts. Gut, 49 (3), 347-353.

Howe, G. R., Hirohata, T., Hislop, T. G., Iscovich, J. M., Yuan, J. M., Katsouyanni, K., … & Shunzhang, Y. (1990). Dietary factors and risk of breast cancer: combined analysis of 12 case—control studies. JNCI: Journal of the National Cancer Institute, 82 (7), 561-569.

Lewallen, S., & Courtright, P. (1998). Epidemiology in practice: case-control studies. Community eye health, 11 (28), 57–58.

Strachan, D. P., & Cook, D. G. (1998). Parental smoking and childhood asthma: longitudinal and case-control studies. Thorax, 53 (3), 204-212.

Tenny, S., Kerndt, C. C., & Hoffman, M. R. (2021). Case Control Studies. In StatPearls . StatPearls Publishing.

Togha, M., Razeghi Jahromi, S., Ghorbani, Z., Martami, F., & Seifishahpar, M. (2018). Serum Vitamin D Status in a Group of Migraine Patients Compared With Healthy Controls: A Case-Control Study. Headache, 58 (10), 1530-1540.

Further Information

  • Schulz, K. F., & Grimes, D. A. (2002). Case-control studies: research in reverse. The Lancet, 359(9304), 431-434.
  • What is a case-control study?

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Case-control and Cohort studies: A brief overview

Posted on 6th December 2017 by Saul Crandon

Man in suit with binoculars

Introduction

Case-control and cohort studies are observational studies that lie near the middle of the hierarchy of evidence . These types of studies, along with randomised controlled trials, constitute analytical studies, whereas case reports and case series define descriptive studies (1). Although these studies are not ranked as highly as randomised controlled trials, they can provide strong evidence if designed appropriately.

Case-control studies

Case-control studies are retrospective. They clearly define two groups at the start: one with the outcome/disease and one without the outcome/disease. They look back to assess whether there is a statistically significant difference in the rates of exposure to a defined risk factor between the groups. See Figure 1 for a pictorial representation of a case-control study design. This can suggest associations between the risk factor and development of the disease in question, although no definitive causality can be drawn. The main outcome measure in case-control studies is odds ratio (OR) .

another name for case control study

Figure 1. Case-control study design.

Cases should be selected based on objective inclusion and exclusion criteria from a reliable source such as a disease registry. An inherent issue with selecting cases is that a certain proportion of those with the disease would not have a formal diagnosis, may not present for medical care, may be misdiagnosed or may have died before getting a diagnosis. Regardless of how the cases are selected, they should be representative of the broader disease population that you are investigating to ensure generalisability.

Case-control studies should include two groups that are identical EXCEPT for their outcome / disease status.

As such, controls should also be selected carefully. It is possible to match controls to the cases selected on the basis of various factors (e.g. age, sex) to ensure these do not confound the study results. It may even increase statistical power and study precision by choosing up to three or four controls per case (2).

Case-controls can provide fast results and they are cheaper to perform than most other studies. The fact that the analysis is retrospective, allows rare diseases or diseases with long latency periods to be investigated. Furthermore, you can assess multiple exposures to get a better understanding of possible risk factors for the defined outcome / disease.

Nevertheless, as case-controls are retrospective, they are more prone to bias. One of the main examples is recall bias. Often case-control studies require the participants to self-report their exposure to a certain factor. Recall bias is the systematic difference in how the two groups may recall past events e.g. in a study investigating stillbirth, a mother who experienced this may recall the possible contributing factors a lot more vividly than a mother who had a healthy birth.

A summary of the pros and cons of case-control studies are provided in Table 1.

another name for case control study

Table 1. Advantages and disadvantages of case-control studies.

Cohort studies

Cohort studies can be retrospective or prospective. Retrospective cohort studies are NOT the same as case-control studies.

In retrospective cohort studies, the exposure and outcomes have already happened. They are usually conducted on data that already exists (from prospective studies) and the exposures are defined before looking at the existing outcome data to see whether exposure to a risk factor is associated with a statistically significant difference in the outcome development rate.

Prospective cohort studies are more common. People are recruited into cohort studies regardless of their exposure or outcome status. This is one of their important strengths. People are often recruited because of their geographical area or occupation, for example, and researchers can then measure and analyse a range of exposures and outcomes.

The study then follows these participants for a defined period to assess the proportion that develop the outcome/disease of interest. See Figure 2 for a pictorial representation of a cohort study design. Therefore, cohort studies are good for assessing prognosis, risk factors and harm. The outcome measure in cohort studies is usually a risk ratio / relative risk (RR).

another name for case control study

Figure 2. Cohort study design.

Cohort studies should include two groups that are identical EXCEPT for their exposure status.

As a result, both exposed and unexposed groups should be recruited from the same source population. Another important consideration is attrition. If a significant number of participants are not followed up (lost, death, dropped out) then this may impact the validity of the study. Not only does it decrease the study’s power, but there may be attrition bias – a significant difference between the groups of those that did not complete the study.

Cohort studies can assess a range of outcomes allowing an exposure to be rigorously assessed for its impact in developing disease. Additionally, they are good for rare exposures, e.g. contact with a chemical radiation blast.

Whilst cohort studies are useful, they can be expensive and time-consuming, especially if a long follow-up period is chosen or the disease itself is rare or has a long latency.

A summary of the pros and cons of cohort studies are provided in Table 2.

another name for case control study

The Strengthening of Reporting of Observational Studies in Epidemiology Statement (STROBE)

STROBE provides a checklist of important steps for conducting these types of studies, as well as acting as best-practice reporting guidelines (3). Both case-control and cohort studies are observational, with varying advantages and disadvantages. However, the most important factor to the quality of evidence these studies provide, is their methodological quality.

  • Song, J. and Chung, K. Observational Studies: Cohort and Case-Control Studies .  Plastic and Reconstructive Surgery.  2010 Dec;126(6):2234-2242.
  • Ury HK. Efficiency of case-control studies with multiple controls per case: Continuous or dichotomous data .  Biometrics . 1975 Sep;31(3):643–649.
  • von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.   Lancet 2007 Oct;370(9596):1453-14577. PMID: 18064739.

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Saul Crandon

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Very well presented, excellent clarifications. Has put me right back into class, literally!

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Very clear and informative! Thank you.

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very informative article.

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Thank you for the easy to understand blog in cohort studies. I want to follow a group of people with and without a disease to see what health outcomes occurs to them in future such as hospitalisations, diagnoses, procedures etc, as I have many health outcomes to consider, my questions is how to make sure these outcomes has not occurred before the “exposure disease”. As, in cohort studies we are looking at incidence (new) cases, so if an outcome have occurred before the exposure, I can leave them out of the analysis. But because I am not looking at a single outcome which can be checked easily and if happened before exposure can be left out. I have EHR data, so all the exposure and outcome have occurred. my aim is to check the rates of different health outcomes between the exposed)dementia) and unexposed(non-dementia) individuals.

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Very helpful information

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Thanks for making this subject student friendly and easier to understand. A great help.

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Thanks a lot. It really helped me to understand the topic. I am taking epidemiology class this winter, and your paper really saved me.

Happy new year.

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Wow its amazing n simple way of briefing ,which i was enjoyed to learn this.its very easy n quick to pick ideas .. Thanks n stay connected

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Saul you absolute melt! Really good work man

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am a student of public health. This information is simple and well presented to the point. Thank you so much.

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very helpful information provided here

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really thanks for wonderful information because i doing my bachelor degree research by survival model

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Quite informative thank you so much for the info please continue posting. An mph student with Africa university Zimbabwe.

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Thank you this was so helpful amazing

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Apreciated the information provided above.

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So clear and perfect. The language is simple and superb.I am recommending this to all budding epidemiology students. Thanks a lot.

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Great to hear, thank you AJ!

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I have recently completed an investigational study where evidence of phlebitis was determined in a control cohort by data mining from electronic medical records. We then introduced an intervention in an attempt to reduce incidence of phlebitis in a second cohort. Again, results were determined by data mining. This was an expedited study, so there subjects were enrolled in a specific cohort based on date(s) of the drug infused. How do I define this study? Thanks so much.

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thanks for the information and knowledge about observational studies. am a masters student in public health/epidemilogy of the faculty of medicines and pharmaceutical sciences , University of Dschang. this information is very explicit and straight to the point

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Case Control Studies

Affiliations.

  • 1 University of Nebraska Medical Center
  • 2 Spectrum Health/Michigan State University College of Human Medicine
  • PMID: 28846237
  • Bookshelf ID: NBK448143

A case-control study is a type of observational study commonly used to look at factors associated with diseases or outcomes. The case-control study starts with a group of cases, which are the individuals who have the outcome of interest. The researcher then tries to construct a second group of individuals called the controls, who are similar to the case individuals but do not have the outcome of interest. The researcher then looks at historical factors to identify if some exposure(s) is/are found more commonly in the cases than the controls. If the exposure is found more commonly in the cases than in the controls, the researcher can hypothesize that the exposure may be linked to the outcome of interest.

For example, a researcher may want to look at the rare cancer Kaposi's sarcoma. The researcher would find a group of individuals with Kaposi's sarcoma (the cases) and compare them to a group of patients who are similar to the cases in most ways but do not have Kaposi's sarcoma (controls). The researcher could then ask about various exposures to see if any exposure is more common in those with Kaposi's sarcoma (the cases) than those without Kaposi's sarcoma (the controls). The researcher might find that those with Kaposi's sarcoma are more likely to have HIV, and thus conclude that HIV may be a risk factor for the development of Kaposi's sarcoma.

There are many advantages to case-control studies. First, the case-control approach allows for the study of rare diseases. If a disease occurs very infrequently, one would have to follow a large group of people for a long period of time to accrue enough incident cases to study. Such use of resources may be impractical, so a case-control study can be useful for identifying current cases and evaluating historical associated factors. For example, if a disease developed in 1 in 1000 people per year (0.001/year) then in ten years one would expect about 10 cases of a disease to exist in a group of 1000 people. If the disease is much rarer, say 1 in 1,000,0000 per year (0.0000001/year) this would require either having to follow 1,000,0000 people for ten years or 1000 people for 1000 years to accrue ten total cases. As it may be impractical to follow 1,000,000 for ten years or to wait 1000 years for recruitment, a case-control study allows for a more feasible approach.

Second, the case-control study design makes it possible to look at multiple risk factors at once. In the example above about Kaposi's sarcoma, the researcher could ask both the cases and controls about exposures to HIV, asbestos, smoking, lead, sunburns, aniline dye, alcohol, herpes, human papillomavirus, or any number of possible exposures to identify those most likely associated with Kaposi's sarcoma.

Case-control studies can also be very helpful when disease outbreaks occur, and potential links and exposures need to be identified. This study mechanism can be commonly seen in food-related disease outbreaks associated with contaminated products, or when rare diseases start to increase in frequency, as has been seen with measles in recent years.

Because of these advantages, case-control studies are commonly used as one of the first studies to build evidence of an association between exposure and an event or disease.

In a case-control study, the investigator can include unequal numbers of cases with controls such as 2:1 or 4:1 to increase the power of the study.

Disadvantages and Limitations

The most commonly cited disadvantage in case-control studies is the potential for recall bias. Recall bias in a case-control study is the increased likelihood that those with the outcome will recall and report exposures compared to those without the outcome. In other words, even if both groups had exactly the same exposures, the participants in the cases group may report the exposure more often than the controls do. Recall bias may lead to concluding that there are associations between exposure and disease that do not, in fact, exist. It is due to subjects' imperfect memories of past exposures. If people with Kaposi's sarcoma are asked about exposure and history (e.g., HIV, asbestos, smoking, lead, sunburn, aniline dye, alcohol, herpes, human papillomavirus), the individuals with the disease are more likely to think harder about these exposures and recall having some of the exposures that the healthy controls.

Case-control studies, due to their typically retrospective nature, can be used to establish a correlation between exposures and outcomes, but cannot establish causation . These studies simply attempt to find correlations between past events and the current state.

When designing a case-control study, the researcher must find an appropriate control group. Ideally, the case group (those with the outcome) and the control group (those without the outcome) will have almost the same characteristics, such as age, gender, overall health status, and other factors. The two groups should have similar histories and live in similar environments. If, for example, our cases of Kaposi's sarcoma came from across the country but our controls were only chosen from a small community in northern latitudes where people rarely go outside or get sunburns, asking about sunburn may not be a valid exposure to investigate. Similarly, if all of the cases of Kaposi's sarcoma were found to come from a small community outside a battery factory with high levels of lead in the environment, then controls from across the country with minimal lead exposure would not provide an appropriate control group. The investigator must put a great deal of effort into creating a proper control group to bolster the strength of the case-control study as well as enhance their ability to find true and valid potential correlations between exposures and disease states.

Similarly, the researcher must recognize the potential for failing to identify confounding variables or exposures, introducing the possibility of confounding bias, which occurs when a variable that is not being accounted for that has a relationship with both the exposure and outcome. This can cause us to accidentally be studying something we are not accounting for but that may be systematically different between the groups.

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Prospective vs. Retrospective Studies

Prospective

A prospective study watches for outcomes, such as the development of a disease, during the study period and relates this to other factors such as suspected risk or protection factor(s). The study usually involves taking a cohort of subjects and watching them over a long period. The outcome of interest should be common; otherwise, the number of outcomes observed will be too small to be statistically meaningful (indistinguishable from those that may have arisen by chance). All efforts should be made to avoid sources of bias such as the loss of individuals to follow up during the study. Prospective studies usually have fewer potential sources of bias and confounding than retrospective studies.

Retrospective

A retrospective study looks backwards and examines exposures to suspected risk or protection factors in relation to an outcome that is established at the start of the study. Many valuable case-control studies, such as Lane and Claypon's 1926 investigation of risk factors for breast cancer, were retrospective investigations. Most sources of error due to confounding and bias are more common in retrospective studies than in prospective studies. For this reason, retrospective investigations are often criticised. If the outcome of interest is uncommon, however, the size of prospective investigation required to estimate relative risk is often too large to be feasible. In retrospective studies the odds ratio provides an estimate of relative risk. You should take special care to avoid sources of bias and confounding in retrospective studies.

Prospective investigation is required to make precise estimates of either the incidence of an outcome or the relative risk of an outcome based on exposure.

Case-Control studies

Case-Control studies are usually but not exclusively retrospective, the opposite is true for cohort studies. The following notes relate case-control to cohort studies:

  • outcome is measured before exposure
  • controls are selected on the basis of not having the outcome
  • good for rare outcomes
  • relatively inexpensive
  • smaller numbers required
  • quicker to complete
  • prone to selection bias
  • prone to recall/retrospective bias
  • related methods are risk (retrospective) , chi-square 2 by 2 test , Fisher's exact test , exact confidence interval for odds ratio , odds ratio meta-analysis and conditional logistic regression .

Cohort studies

Cohort studies are usually but not exclusively prospective, the opposite is true for case-control studies. The following notes relate cohort to case-control studies:

  • outcome is measured after exposure
  • yields true incidence rates and relative risks
  • may uncover unanticipated associations with outcome
  • best for common outcomes
  • requires large numbers
  • takes a long time to complete
  • prone to attrition bias (compensate by using person-time methods)
  • prone to the bias of change in methods over time
  • related methods are risk (prospective) , relative risk meta-analysis , risk difference meta-analysis and proportions

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another name for case control study

  • Health and social care
  • Public health
  • Health improvement

Case-control study: comparative studies

How to use a case-control study to evaluate your digital health product.

This page is part of a collection of guidance on evaluating digital health products .

A case-control study is a type of observational study. It looks at 2 sets of participants. One group has the condition you are interested in (the cases) and one group does not have it (the controls).

In other respects, the participants in both groups are similar. You can then look at a particular factor that might have caused the condition, such as your digital product, and compare participants from the 2 groups in relation to that.

A case-control study is an observational study because you observe the effects on existing groups rather than designing an experiment where participants are allocated into different groups.

What to use it for

A case-control study can help you to find out if your digital product or service achieves its aims, so it can be useful when you have developed your product (summative evaluation).

It can be a useful method when it would be difficult or impossible to randomise participants, for example, if your product aims to help people with rare health conditions.

Case-control studies have many benefits.

  • help to estimate the effects of your digital product when randomisation is not possible
  • use existing data, which could be cheaper and easier
  • operate with fewer participants compared to other designs

There can also be drawbacks of a case-control study.

For example:

  • you need to pay careful attention to factors that may influence your results, confounding factors and biases – see explanation in ‘How to carry out a case-control study’ below
  • there may be challenges when accessing pre-existing data
  • you cannot draw definitive answers about the effects of your product as you haven’t randomly selected participants for your evaluation

How to carry out a case-control study

In a traditional case-control design, cases and controls are looked at retrospectively – that is, the health condition and the factor that might have caused it have already occurred when you start the study.

Sources of cases and controls typically include:

  • routinely collected data at medical facilities
  • disease registries
  • cross-sectional surveys

Some researchers use the term prospective case-control study when, for example, a prospective group exposed to an intervention is compared to a retrospective control.

Choosing your control

Selecting an appropriate control is an important part of a case-control study. The comparison group should be as similar as possible to the source population that produced the cases. This means the participants will be similar to each other in terms of factors that may influence the outcomes you’re looking at. Ideally, they will only differ in whether they received your digital product (cases) or not (controls).

There are 2 main types of case-control design: matched and unmatched.

Essentially, in an unmatched case-control design, a shared control group is selected for all cases at random given certain attributes. In a matched case-control design, controls are selected case-by-case based on specified characteristics. You should pick characteristics that have an effect on the usage of digital devices and services.

Commonly used matching factors include:

  • socio-economic status

However, think about other characteristics and attributes that might influence the use of your product, and the subsequent outcomes.

Confounding variables and biases

Confounding variables (variables other than the one you are interested in that may influence the results) and biases (errors that influence the sample selected and results observed) are important to consider when conducting any research. This is especially important in designs that are non-randomised.

  • selection bias can happen when participants are assigned without randomisation
  • attribution bias may occur when patients with unfavourable outcomes are less likely to attend follow-ups

Analysing your data

The analysis most commonly used in case-control studies is an odds ratio, which is the chance (odds) of the outcomes occurring in the case group versus the control group.

Example: Can telemedicine help with post-bariatric surgery care? A case-control design

In 2019, Wang and colleagues published a paper entitled Exploring the Effects of Telemedicine on Bariatric Surgery Follow-up: a Matched Case Control Study .

The study showed that people who go through bariatric surgery have better outcomes if they attend their follow-up appointments after surgery in comparison to those who do not. However, attending appointments can be challenging for people who live in remote areas. In Ontario, Canada, telemedicine suites were set up to enable healthcare provider-patient videoconferencing.

The researchers used a matched case-control study to investigate if telemedicine videoconferencing can support post-surgery appointment attendance rates in people who live further away from the hospital sites. They used the existing data from the bariatric surgery hospital programme to identify eligible patients.

All patients attending the bariatric surgery were offered telemedicine services. The cases were the participants who used telemedicine services; they were compared to those who did not (the controls).

Cases and controls were matched on various characteristics, specifically:

  • time since bariatric surgery
  • body mass index ( BMI )
  • travel distance from the hospital site

Researchers measured:

  • the percentage of appointments attended
  • rates of dropout
  • pre-and post-surgery weight and BMI
  • various physical and psychological outcomes

They also calculated rurality index to classify patients into urban, non-urban and rural areas. These variables were used to compare cases (those who used telemedicine) and controls (those who did not).

During the study period, they identified that 487 patients of 1,262 who received bariatric surgery used telemedicine services. Of those, 192 agreed to participate in the study.

They found that patients who used telemedicine did as well as patients who attended in person, both in terms of appointment attendance rates and in terms of physical and psychological outcomes.

Moreover, the researchers found that the cases (telemedicine users) came from more rural areas than the controls. The authors argued that this demonstrated that telemedicine can help overcome the known challenges for patients in more rural areas to attend appointments.

Randomising patients to telemedicine or withdrawing the telemedicine would be difficult, undesirable and possibly unethical. Case-control was a good alternative to assess the potential impact on patient outcomes in a service that is already up and running.

More information and resources

A 2003 study by Mann provides an accessible overview of observational research methods, including an explanation of biases and confounding variables.

On the website for Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ), there is a checklist of items that should be included in reports of case-control studies .

A 2016 study by Pearce offers considerations for the analysis of a matched case-control study.

Examples of case-control studies in digital health

In a 2020 study by Heuvel and others , researchers assessed a new digital health tool to monitor women at increased risk of preeclampsia at home. They investigated if the digital tool allows for fewer antenatal visits without compromising women’s safety, and whether it positively affects pregnancy outcomes. This study used a prospective case group compared to a retrospective control group.

In a 2019 study by Depp and others , the research team examined whether schizophrenia symptoms were associated with mobility (measured using GPS sensors). They compared participants with schizophrenia to healthy controls and they found that less mobility was associated with greater symptoms of schizophrenia.

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  • Curr Control Trials Cardiovasc Med
  • v.2(3); 2001

Bridging case-control studies and randomized trials

Frits r rosendaal.

1 Leiden University Medical Center (LUMC), Department of Clinical Epidemiology, C0-P, PO Box 9600, 2300 RC Leiden, The Netherlands

Randomized trials and observational studies, such as case-control studies, are often seen as opposing approaches. However, in many instances results obtained by different designs may complement each other. For instance, case-control studies on aetiology of disease may help to give the direction of future trials. In this commentary, the author discusses the purpose of randomization and observation, and under which conditions one design may be preferred to another. Randomization is useful to combat 'confounding by indication', and is therefore the design of choice for most therapeutic trials. When this confounding is not an issue, as in studies of genetic risk factors or side-effects, then case-control studies are preferred.

In this issue of Current Controlled Trials in Cardiovascular Medicine , Ray et al [ 1 ] report the results of a study on genetic and acquired risk factors for venous thrombosis in women. This paper is remarkable, not only because it focuses on women, but also because it is an observational, case-control study rather than a randomized trial.

In their editorial in the first issue of the journal, editors-in-chief Curt Furberg and Bertram Pitt did not explicitly mention randomized trials - they spoke of a journal for 'clinical trials' [ 2 ]. This suggests experimental rather than observational studies, but does not necessarily imply randomization. Nevertheless, by encouraging prospective authors to report trial results according to the Consolidated Standards of Reporting Trials guidelines [ 3 ], they implicitly made it clear that the journal was aimed at reporting randomized clinical trials.

Does this publication therefore represent a major change in policy? Did it take only a handful of issues before the editors decided to 'lower' their standards? I think not. Sir Austin Bradford Hill is credited with performing the first properly randomized trial in 1948 [ 4 ], although studies with some form of random treatment allocation antedated it by at least 50 years [ 5 ]. When we read his Principles of Medical Statistics , from the first edition in 1937 [ 6 ] to the last posthumous edition of 1984 [ 7 ], we see an increasing emphasis on randomization, the use of placebo controls and double blinding. However, even as a strong advocate for experimentation, he defined a clinical trial as a study in which we learn from a patient; up to the 12th edition he continued to quote the 1949 Presidential Address to the Royal Society of Medicine by Sir George Pickering, who argued that all that happened to a patient should be recorded.

Randomization is a tool, not a goal in and of itself. The goal of clinical research is to obtain an answer that is valid and precise, and the ultimate goal is to prevent and treat disease in the best way. Each study design has indications and contraindications. The main threats to validity in treatment studies are regression to the mean (ie improvement due to the natural course of a disorder) and 'confounding by indication' (ie incomparability of groups when the risk profile affects the choice of drug). Control groups are included to address regression to the mean, whereas randomization is aimed at creating groups with similar prognosis to combat confounding by indication. In clinical practice, physicians tailor treatment to a patient's prognosis, and so a simple comparison of patients treated with different regimens will often be biased. Because of the need to counter this confounding by indication, randomization has become nearly synonymous with good research into medical therapies. Many have broadened this to the belief that randomization is synonymous with good research, and have created a hierarchy of study designs. This is a mistake. First, randomized trials do have drawbacks. Secondly, they are not always possible, or, for that matter, ethical.

One important drawback of randomized trials is that they typically involve patients who were considered fit to enter, were likely to finish the trial, and believed, or even shown during a run-in phase, to comply with the medications. This population is quite different from the patients in the waiting room. Another important drawback is that, because the precision of an estimate is dependent on the number of patients experiencing an event, randomized trials, unless they are very large, will seldom be precise. A third drawback is that in all prospective studies, including randomized trials, it is seldom possible to relate the outcome of interest to determinants that occurred immediately before that outcome, and that might even have interacted in producing it (for instance lifestyle factors, intercurrent disease). In some cases, randomization is simply not possible, as in aetiological studies of genetic variants. Also, even for nongenetic risk factors, randomization would often lead to ethical problems (for instance, studies on the effects of alcohol).

Case-control studies, such as the one on venous thrombosis published in the present issue [ 1 ], have other indications and contraindications. In this type of study, patients with the outcome of interest are contrasted to those without, and therefore the precision of the estimate is much greater. Ideally, all patients in a certain geographical region are included, so generalizibility is better. Finally, in contrast to randomized trials and other cohort studies, patients can be seen shortly after the event and recent risk factors can be recorded.

Case-control studies also have drawbacks; if the disease changes the risk factor measurement, then inference becomes difficult (for instance, varicose veins are often seen after a deep vein thrombosis, but are probably not a cause of venous thrombosis). In studies of treatments, case-control studies, like all observational studies, may be subject to bias through confounding by indication. It is important to make a distinction between expected or intended effects (efficacy), and unintended or unexpected effects (side effects). Although in the case of efficacy confounding by indication is a likely source of bias, this is not so in the case of side effects. If physicians or patients neither intend nor expect a certain effect of a drug, then the presence of risk factors for that effect is unlikely to affect prescription, and therefore groups using and not using the drug will be comparable, and estimates will be unbiased. This can be illustrated with the effects of hormone replacement therapy. A large observational study (the Nurses' Health study) showed a strong protective effect on coronary heart disease [ 8 ] that was not confirmed in a randomized trial [ 9 ]. Both studies found very similar relative risks of venous thrombosis, which was an unexpected side effect [ 10 , 11 ].

Genetic studies on the aetiology of disease and side effects of drugs are needed to direct or complement randomized trials of therapies. For both such study types the case-control design is the best choice. It is therefore appropriate that case-control studies and randomized controlled trials are published side by side, in order to serve our ultimate goal of improving patient care.

  • Ray JG, Langman L, Vermeulen MJ, Evrovski J, Yeo E, Cole DEC. Genetics University of Toronto Thrombophilia Study in Women (GUTTSI): genetic and other risk factors for venous thromboembolism in women. Curr Control Clin Trials Cardiovasc Med. 2001; 2 :141–149. doi: 10.1186/CVM-2-3-141. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Furberg C, Pitt B. Current Controlled Trials in Cardiovascular Medicine : a new journal for a new age (http://cvm.controlled-trials.com). Current Controlled Trials in Cardiovascular Medicine. 2000; 1 :1–2. doi: 10.1186/CVM-1-1-001. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Begg C, Cho M, Eastwood ELS, Horton R, Moher D, Olkin I, Pitkin R, Rennie D, Schulz K, Simel D, Stoup D. Improving the quality of reporting of randomised controlled trials. The CONSORT statement. JAMA. 1996; 276 :637–639. doi: 10.1001/jama.276.8.637. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Medical Research Council Streptomycin treatment of pulmonary tuberculosis. Br Med J. 1948; ii :769–782. [ PMC free article ] [ PubMed ] [ Google Scholar ]
  • Fibiger J. On treatment of diptheria with serum [in Danish]. Hospitalstidende. 1898; 6 :309–325. [ Google Scholar ]
  • Hill AB. Principles of Medical Statistics, 1st ed London: Lancet; 1937.
  • Hill AB, Hill ID. Principles of Medical Statistics 12th ed London: Edward Arnold; 1984.
  • Stampfer MJ, Willett WC, Colditz GA, Rosner B, Speizer FE, Hennekens CH. A prospective study of postmenopausal estrogen therapy and coronary heart disease. N Engl J Med. 1985; 313 :1044–1049. [ PubMed ] [ Google Scholar ]
  • Hulley S, Grady D, Bush T, Furberg C, Herrington D, Riggs B, Vit-tinghoff E, for the Heart and estrogen/progestin Replacement Study (HERS) Research Group Randomized trial of estrogen plus progestin for secondary prevention of coronary heart disease in postmenopausal women. JAMA. 1998; 280 :605–613. doi: 10.1001/jama.280.7.605. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Grodstein F, Stampfer MJ, Goldhaber SZ, Manson JE, Colditz GA, Speizer FE, Willett WC, Hennekens CH. Prospective study of exogenous hormones and risk of pulmonary embolism in women. Lancet. 1996; 348 :983–987. doi: 10.1016/S0140-6736(96)07308-4. [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Grady D, Wenger NK, Herrington D, Khan S, Furberg C, Hunninghoke D, Vittinghoff E, Hulley S. Postmenopausal hormone therapy increases risk for venous thromboembolic disease. Ann Intern Med. 2000; 132 :689–696. [ PubMed ] [ Google Scholar ]

IMAGES

  1. Case Control

    another name for case control study

  2. What is a Case Control Study?

    another name for case control study

  3. PPT

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  4. PPT

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  6. PPT

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VIDEO

  1. Case Control Study (Lecture

  2. 3 Intro to use case

  3. District Manager Case Study Workshop

  4. Case Studies

  5. Case Control Study Part 1

  6. Case-control study design

COMMENTS

  1. 99 Words and Phrases for Case-control Study

    Case-control Study synonyms - 99 Words and Phrases for Case-control Study sentences Parts of speech case-control analysis n. case-control audit n. case-control examination n. case-control inquiry n. case-control investigation n. case-control query n. case-control research n. case-control review n. case-control survey n. case-control trial n.

  2. What Is a Case-Control Study?

    Case-control studies are a type of observational study often used in fields like medical research, environmental health, or epidemiology. While most observational studies are qualitative in nature, case-control studies can also be quantitative, and they often are in healthcare settings.

  3. Case Control Studies

    A case-control study is a type of observational study commonly used to look at factors associated with diseases or outcomes. [1] The case-control study starts with a group of cases, which are the individuals who have the outcome of interest.

  4. Case-control study

    A case-control study (also known as case-referent study) is a type of observational study in which two existing groups differing in outcome are identified and compared on the basis of some supposed causal attribute.

  5. A Practical Overview of Case-Control Studies in Clinical Practice

    Case-control studies are one of the major observational study designs for performing clinical research. The advantages of these study designs over other study designs are that they are relatively quick to perform, economical, and easy to design and implement. Case-control studies are particularly appropriate for studying disease outbreaks, rare diseases, or outcomes of interest. This article ...

  6. Case Control Study: Definition & Examples

    Examples FAQs A case-control study is a research method where two groups of people are compared - those with the condition (cases) and those without (controls). By looking at their past, researchers try to identify what factors might have contributed to the condition in the 'case' group. Definition

  7. Case Control Study: Definition, Benefits & Examples

    By Jim Frost 2 Comments What is a Case Control Study? A case control study is a retrospective, observational study that compares two existing groups. Researchers form these groups based on the existence of a condition in the case group and the lack of that condition in the control group.

  8. A Practical Overview of Case-Control Studies in Clinical Practice

    General Overview of Case-Control Studies. In observational studies, also called epidemiologic studies, the primary objective is to discover and quantify an association between exposures and the outcome of interest, in hopes of drawing causal inference. Observational studies can have a retrospective study design, a prospective design, a cross ...

  9. Epidemiology in Practice: Case-Control Studies

    A case-control study is designed to help determine if an exposure is associated with an outcome (i.e., disease or condition of interest). In theory, the case-control study can be described simply. First, identify the cases (a group known to have the outcome) and the controls (a group known to be free of the outcome).

  10. Methodology Series Module 2: Case-control Studies

    Introduction Case-Control study design is a type of observational study design. In an observational study, the investigator does not alter the exposure status. The investigator measures the exposure and outcome in study participants, and studies their association. Go to: Design

  11. Case-control study in medical research: Uses and limitations

    Other terms used to describe case-control studies include epidemiological, retrospective, and observational. What is a case-control study? A case-control study can help provide...

  12. A Practical Overview of Case-Control Studies in Clinical Practice

    Abbreviation platelet-activating factor acetylhydrolase General Overview of Case-Control Studies In observational studies, also called epidemiologic studies, the primary objective is to discover and quantify an association between exposures and the outcome of interest, in hopes of drawing causal inference.

  13. 10 Words and Phrases for Case Control Study

    definitions sentences thesaurus suggest new epidemiological study matched case-control study nested case-control study observational study retrospective study case-cohort study case-comparison study case-history study case-referent study population-based case-control study Another way to say Case Control Study?

  14. Case-control and Cohort studies: A brief overview

    Case-control and cohort studies are observational studies that lie near the middle of the hierarchy of evidence. These types of studies, along with randomised controlled trials, constitute analytical studies, whereas case reports and case series define descriptive studies (1).

  15. Case Control Studies

    A case-control study is a type of observational study commonly used to look at factors associated with diseases or outcomes. The case-control study starts with a group of cases, which are the individuals who have the outcome of interest.

  16. Prospective, Retrospective, Case-control, Cohort Studies

    Cohort studies are usually but not exclusively prospective, the opposite is true for case-control studies. The following notes relate cohort to case-control studies: outcome is measured after exposure yields true incidence rates and relative risks may uncover unanticipated associations with outcome best for common outcomes expensive

  17. Case-control study

    case-control study, in epidemiology, observational (nonexperimental) study design used to ascertain information on differences in suspected exposures and outcomes between individuals with a disease of interest (cases) and comparable individuals who do not have the disease (controls). Analysis yields an odds ratio (OR) that reflects the relative probabilities of exposure in the two populations.

  18. Observational Studies: Cohort and Case-Control Studies

    Cohort studies and case-control studies are two primary types of observational studies that aid in evaluating associations between diseases and exposures. In this review article, we describe these study designs, methodological issues, and provide examples from the plastic surgery literature. Keywords: observational studies, case-control study ...

  19. An Introduction to the Fundamentals of Cohort and Case-Control Studies

    Design. In a case-control study, a number of cases and noncases (controls) are identified, and the occurrence of one or more prior exposures is compared between groups to evaluate drug-outcome associations ( Figure 1 ). A case-control study runs in reverse relative to a cohort study. 21 As such, study inception occurs when a patient ...

  20. Case-control study: comparative studies

    A case-control study is a type of observational study. It looks at 2 sets of participants. One group has the condition you are interested in (the cases) and one group does not have it (the controls).

  21. Nested case-control studies (Chapter 7)

    D. R. Cox Chapter Get access Share Cite Summary The nested case-control design accommodates case event times into the sampling of controls. In this design one or more controls is or are selected for each case from the risk set at the time at which the case event occurs. Controls may also be matched to cases on selected variables.

  22. Design and data analysis case-controlled study in clinical research

    Introduction. Clinicians think of case-control study when they want to ascertain association between one clinical condition and an exposure or when a researcher wants to compare patients with disease exposed to the risk factors to non-exposed control group. In other words, case-control study compares subjects who have disease or outcome (cases ...

  23. Bridging case-control studies and randomized trials

    Randomized trials and observational studies, such as case-control studies, are often seen as opposing approaches. However, in many instances results obtained by different designs may complement each other. For instance, case-control studies on aetiology of disease may help to give the direction of future trials.