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A Review Study on Confounding Effect: Case-control Study.
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Seonwoo Kim, Minji Kim, Soon Young Lee
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Korean J Epidemiol. 1999;21(2):248-253.
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Abstract
Confounding is the distortion of a disease/exposure association brought about by other factors which are not considered in the study design or the data analysis. These factors are called confounding factors. We should be cautious in data analysis of observational study of association of disease/exposure, since confounding often occurred in observational study. This study examines confounding effect according to data pattern (the ratio of controls to cases, the ratio of exposures to non-exposures for each level of confounding factor), criteria for treating a variable as a confounding variable, and some notes for the analysis in case-control study.
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A Review Study on Comparing Treatment Effects among Subgroups.
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Seonwoo Kim, Minji Kim, Soon Young Lee
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Korean J Epidemiol. 1999;21(1):104-110.
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Abstract
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Abstract
It is interested in examining treatment effect on a particular category of subjects or in comparing treatment effects among different subgroups as well as overall treatment effect due to heterogeneity of study subjects.
Subgroup analyses are exceedingly common, but they are also often misleading. Conclusions based on subgroup analyses can do harm both when a particular category of people is denied effective treatment (a "false-negative" conclusion), and when ineffective or even harmful treatment is given to a subgroup of people (a "false-positive" conclusion). Because of the frequency and the importance of clinical application of subgroup analysis, researchers need to be cautious about doing subgroup analyses. This study presents guidelines to help conducting subgroup analyses correctly.
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KSE
