Case-Control Studies - AMA Manual of Style

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Case-Control Studies 

Case-Control Studies

Chapter:
Study Design and Statistics
Author(s):

Margaret A. Winker

and Stephen J. Lurie

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Case-Control Studies

Case-control studies, which are always retrospective, compare those who have had an outcome or event (cases) with those who have not (controls). Cases and controls are then evaluated for exposure to various risk factors and thus should never be selected on the basis of their exposure to the risk factors under investigation. Cases and controls generally are matched according to specific characteristics (eg, age, sex, or duration of disease) to reduce confounding by these variables. However, if the matched variables are inextricably linked with the exposure of interest (not necessarily with the disease or outcome of interest), matching may confound the analysis (see also overmatching). The independent variable is exposure to an item of interest (eg, a drug or disease). Information about the source of both cases and controls must be included, and inclusion and exclusion criteria must be listed for each. Cases and controls should be drawn from the same or similar populations to avoid selection bias. Pairs (1:1 match) or groups (eg, 1:2 or 1:3 match) of cases and controls may be matched on 1 or more variables. The analysis generally is unpaired, however, because of the difficulty in matching every important characteristic. Nonetheless, paired analysis reduces the necessary sample size to detect a difference and may be justified if individuals are well matched. Recall bias is common in all retrospective studies and is especially a concern when participants believe that a factor related to the independent variable may be associated with the outcome. If recall bias may have occurred, the authors should discuss how they addressed this possibility.

In a nested case-control study, the cases and controls are drawn from some larger population or cohort that may have been convened for some other purpose. In these instances, authors should clearly indicate how the original sample was defined, the size of the original sample, and how the cases and controls were selected from it.

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