Power and sample size calculations in case-control studies of gene-environment interactions: comments on different approaches.
Power and sample size calculations in case-control studies of gene-environment interactions: comments on different approaches.
复制标题
DOI：
10.1093/oxfordjournals.aje.a009876
复制
发表时间：
1999-04
影响因子：
5
通讯作者：
Montserrat Garcfa-Closas;J. Lubin
中科院分区：
文献类型：
--
作者：
Montserrat Garcfa-Closas;J. Lubin
功效和样本量的考虑对于基因-环境相互作用的流行病学研究的设计至关重要。黄等人。 (Am J Epidemiol 1994;140:1029-37) 以及 Foppa 和 Spiegelman (Am J Epidemiol 1997;146:596-604) 提出了基因-环境相互作用的病例对照研究的功效和样本量计算。使用这些方法的计算与 Lubin 和 Gail 先前发表的优势比通用多元回归模型方法（Am J Epidemiol 1990；131：552-66）的比较显示，在某些情况下存在显着差异。这些差异是 Hwang 等人对零假设进行高度限制性表征的结果。以及 Foppa 和 Spiegelman，这导致低估了样本量并高估了基因-环境相互作用测试的功效。美国国家癌症研究所将在不久的将来免费提供一种计算机程序，用于执行样本量和功效计算，以使用 Lubin 和 Gail 方法检测基因-环境相互作用的加法或乘法模型。
Power and sample size considerations are critical for the design of epidemiologic studies of gene-environment interactions. Hwang et al. (Am J Epidemiol 1994;140:1029-37) and Foppa and Spiegelman (Am J Epidemiol 1997;146:596-604) have presented power and sample size calculations for case-control studies of gene-environment interactions. Comparisons of calculations using these approaches and an approach for general multivariate regression models for the odds ratio previously published by Lubin and Gail (Am J Epidemiol 1990; 131:552-66) have revealed substantial differences under some scenarios. These differences are the result of a highly restrictive characterization of the null hypothesis in Hwang et al. and Foppa and Spiegelman, which results in an underestimation of sample size and overestimation of power for the test of a gene-environment interaction. A computer program to perform sample size and power calculations to detect additive or multiplicative models of gene-environment interactions using the Lubin and Gail approach will be available free of charge in the near future from the National Cancer Institute.