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Case-control matching: effects, misconceptions, and recommendations.

Mohammad Ali Mansournia1, Nicholas Patrick Jewell2,3, Sander Greenland4,5

  • 1Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, PO Box 14155-6446, Tehran, Iran. mansournia_ma@yahoo.com.

European Journal of Epidemiology
|November 5, 2017
PubMed
Summary
This summary is machine-generated.

Matching in case-control studies can introduce selection bias and distort results, unlike in cohort studies. Researchers should limit matching to strong confounders to avoid these issues.

Keywords:
BiasCase–control studiesConfoundingMatchingOdds ratio

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Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Case-control matching is widely used but often misunderstood.
  • Subtle issues arise with case-control matching that differ from matched cohort studies.

Purpose of the Study:

  • To elucidate common misconceptions regarding case-control matching.
  • To highlight specific problems introduced by matching in case-control designs.
  • To contrast these issues with those in matched cohort studies.

Main Methods:

  • Discussion of potential biases and statistical distortions.
  • Comparison of matching effects in case-control versus cohort studies.
  • Review of methods for unbiased estimation and efficiency.

Main Results:

  • Matching can induce selection bias, even for non-confounders.
  • Matching distorts dose-response relationships and can reduce precision.
  • Unbiased estimation requires careful consideration of matching protocols and residual confounding.
  • Sparse-data bias can affect matched analyses.

Conclusions:

  • Case-control matching should be restricted to a few strong confounders.
  • No matching is preferable if no strong confounders are identified.
  • Matched case-control studies allow assessment of odds ratio modification and absolute rates under certain conditions.