Interpreting the term selection bias in medical research
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Updated: Jul 25, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
1American Medical Association, Chicago, USA.
Abstract:
The issue of selection bias is often raised in the critical appraisal of medical studies, but it is often poorly defined and misunderstood. This paper, describes three common patterns of use of the term selection bias and their effects on study results. The three ways in which selection bias is used are related to 1) selection of representative subjects, 2) selection of subjects to exposures, and 3) selection of subjects at outcome. Avoidance of bias in the first of these issues, selection of representative subjects, enhances the ability to generalize a study's results. The other two uses of selection bias relate to the internal validity of studies. The selection of subjects to exposures without randomization in observational studies can distort results because of confounding variables. The selection of study subjects at outcome in case-control and cross-sectional studies can distort study findings if selection into the study is distorted according to exposure status. Readers of medical studies should understand the different implications of these uses to improve their critical evaluation of studies. Writers and discussants should be aware of these differences and provide clarifying details when they use the term.
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