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Related Experiment Videos

Selecting controls for assessing interaction in nested case-control studies.

John Cologne1, Bryan Langholz

  • 1Department of Statistics, Radiation Effects Research Foundation, 5-2 Hijiyama Park, Minami-ku, Hiroshima 732-0815, Japan.

Journal of Epidemiology
|August 26, 2003
PubMed
Summary
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Counter-matching controls in nested case-control studies is more efficient for studying risk factor interactions than traditional matching or random sampling, especially for rare factors.

Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Nested case-control studies are used to investigate risk factors.
  • Matching and counter-matching are control selection strategies.
  • Interactions between risk factors are of interest.

Purpose of the Study:

  • Compare matching and counter-matching for selecting controls.
  • Evaluate efficiency in nested case-control studies.
  • Assess risk factor interaction inference.

Main Methods:

  • Simulations and asymptotic relative efficiency calculations were used.
  • Dichotomous risk factors X and Z were analyzed.
  • General models for joint risk were employed.

Main Results:

Related Experiment Videos

  • Counter-matching demonstrated superior efficiency for interaction inference with rare, uncorrelated risk factor X.
  • Counter-matching is generally more efficient than matched designs for studying interactions.
  • Performance was compared to matching and random sampling.

    • Conclusions:

    • Counter-matching is a superior alternative to matching for studying interactions in nested case-control studies.
    • Counter-matched designs allow standard statistical analysis and confounding investigation.
    • Matched designs require non-standard approaches for general risk models.