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Activity Number: 61 - Approaches for Modeling Clustered and Longitudinal Data
Type: Contributed
Date/Time: Monday, August 3, 2020 : 10:00 AM to 2:00 PM
Sponsor: Biometrics Section
Abstract #313003
Title: Comparison of Tests for Association of 2 by 2 Tables Under the Multiple Testing Setting
Author(s): Huan Cheng* and Jianghua He
Companies: University of Kansas Medical Center and University of Kansas Medical Center
Keywords: 2 by 2 contingency table; unconditional exact test; fisher’s exact test; Benjamini-Hochberg procedure; multiple testing

In the single test setting, many studies have shown that the asymptotic Pearson’s chi-squared test cannot preserve the test size for small samples and Fisher Exact test tends to be overly conservative. Multiple unconditional exact tests were proposed for small samples as they perform better than the commonly used chi-square and Fisher’s exact test. No comparison of these approaches has been done in the multiple testing setting. This study examines the performances of two unconditional tests (Boschloo and Z-pooled test statistics are used) with the Fisher Exact test as well as asymptotic Pearson’s Chi-squared test in a small sample multiple testing scenario via a simulation study. Benjamini-Hochberg (BH) procedure is applied to control the false discovery rate (FDR). The results show that in terms of sensitivity rate, the performances of Z-pooled and Boschloo Statistic are close to each other; the Asymptotic chi-squared test is slightly better than the unconditional exact tests; Fisher Exact test is the least powerful in all different settings. Boschloo’s test is more computation-intensive. The Z-pooled test is more recommended if the running time is a concern.

Authors who are presenting talks have a * after their name.

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