Case-control study - Wikipedia, Case study controlled experiment
Case study controlled experiment
In the social sciences and life sciences, a case study is a research method involving an up-close, in-depth, and detailed examination of a subject of study (the case ...
If I somehow had exposure and outcome information on all of the subjects in the source population and looked at the association using a cohort design, it might look like this:
For example, in a study trying to show that people who smoke (the attribute ) are more likely to be diagnosed with lung cancer (the outcome ), the cases would be persons with lung cancer, the controls would be persons without lung cancer (not necessarily healthy), and some of each group would be smokers. If a larger proportion of the cases smoke than the controls, that suggests, but does not conclusively show, that the hypothesis is valid.
In doing case study research, the "case" being studied may be an individual, organization, event, or action, existing in a specific time and place. For instance, clinical science has produced both well-known case studies of individuals and also case studies of clinical practices.    However, when "case" is used in an abstract sense, as in a claim, a proposition, or an argument, such a case can be the subject of many research methods, not just case study research. Case studies may involve both qualitative and quantitative research methods.
A nested-case control study depends on the pre-existence of a cohort that has been followed over time. This cohort, at its inception or during the course of follow-up, has had exposure information and/or biospecimens collected of interest to the investigator. The investigator identifies cases of disease that occurred in the cohort during the follow-up period. The investigator also identifies disease-free individuals within the cohort to serve as controls. Using previously collected data and obtaining additional measurements of exposures from available biospecimens, the investigator compares the exposure frequencies in cases and controls as in a non-nested case-control study.
Care should be taken to avoid confounding, which arises when an exposure and an outcome are both strongly associated with a third variable. Controls should be subjects who might have been cases in the study but are selected independent of the exposure. Cases and controls should also not be "over-matched."
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In a situation like this a case-control design is a much more efficient option. The investigators identified as many cases as possible (19 agreed to answer the questionnaire), and they selected a sample of 38 non-diseased people as a comparison group (the controls). In this case, the "controls" were non-diseased people who were matched to the cases with respect to age, gender, and neighborhood of residence. Investigators then ascertained the prior exposures of subjects in each group, focusing on food establishments and other possibly relevant exposures they had had during the past two months.
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:
With case-control studies, we essentially work down the columns of the 2 × 2 table. Cases are identified first, then controls. The investigator then determines whether cases and controls were exposed or not exposed to the risk factor. We calculate the odds of exposure among cases (A/C) and the odds of exposure among controls (B/D). The odds ratio is then (A/C)/(B/D), which simplifies, after cross-multiplication, to (A*D)/(B*C).
Measurement of exposure can be made more comparable by using patients with other diseases as controls, especially if subjects are not told the exact focus of the investigation. However, their exposures may be unrepresentative. To give an extreme example, a case-control study of bladder cancer and smoking could give quite erroneous findings if controls were taken from the chest clinic. If other patients are to be used as referents, it is safer to adopt a range of control diagnoses rather than a single disease group. In that way, if one of the control diseases happens to be related to a risk factor under study, the resultant bias is not too large.
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Study Design 101 - Case Control
Case study - Wikipedia
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case study controlled experiment
case study controlled experiment