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Estimating Risks and Relative Risks in Case-Base Studies under the Assumptions of Gene-Environment Independence and Hardy-Weinberg Equilibrium

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  • Tina Tsz-Ting Chui
  • Wen-Chung Lee

Abstract

Many diseases result from the interactions between genes and the environment. An efficient method has been proposed for a case-control study to estimate the genetic and environmental main effects and their interactions, which exploits the assumptions of gene-environment independence and Hardy-Weinberg equilibrium. To estimate the absolute and relative risks, one needs to resort to an alternative design: the case-base study. In this paper, the authors show how to analyze a case-base study under the above dual assumptions. This approach is based on a conditional logistic regression of case-counterfactual controls matched data. It can be easily fitted with readily available statistical packages. When the dual assumptions are met, the method is approximately unbiased and has adequate coverage probabilities for confidence intervals. It also results in smaller variances and shorter confidence intervals as compared with a previous method for a case-base study which imposes neither assumption.

Suggested Citation

  • Tina Tsz-Ting Chui & Wen-Chung Lee, 2014. "Estimating Risks and Relative Risks in Case-Base Studies under the Assumptions of Gene-Environment Independence and Hardy-Weinberg Equilibrium," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-5, August.
    • Handle: RePEc:plo:pone00:0105398
    DOI: 10.1371/journal.pone.0105398
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    References listed on IDEAS

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    1. Nilanjan Chatterjee & Raymond J. Carroll, 2005. "Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies," Biometrika, Biometrika Trust, vol. 92(2), pages 399-418, June.
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