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Marginal screening of 2 × 2 tables in large‐scale case‐control studies

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  • Ian W. McKeague
  • Min Qian

Abstract

Assessing the statistical significance of risk factors when screening large numbers of 2×2 tables that cross‐classify disease status with each type of exposure poses a challenging multiple testing problem. The problem is especially acute in large‐scale genomic case‐control studies. We develop a potentially more powerful and computationally efficient approach (compared with existing methods, including Bonferroni and permutation testing) by taking into account the presence of complex dependencies between the 2×2 tables. Our approach gains its power by exploiting Monte Carlo simulation from the estimated null distribution of a maximally selected log‐odds ratio. We apply the method to case‐control data from a study of a large collection of genetic variants related to the risk of early onset stroke.

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  • Ian W. McKeague & Min Qian, 2019. "Marginal screening of 2 × 2 tables in large‐scale case‐control studies," Biometrics, The International Biometric Society, vol. 75(1), pages 163-171, March.
    • Handle: RePEc:bla:biomet:v:75:y:2019:i:1:p:163-171
    DOI: 10.1111/biom.12957
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