Zou G Y
Robarts Clinical Trials, Robarts Research Institute, PO Box 5015, 100 Perth Drive, London, Ontario, Canada N6A 5K8.
Ann Hum Genet. 2006 Mar;70(Pt 2):262-76. doi: 10.1111/j.1529-8817.2005.00213.x.
This paper applies a retrospective logistic regression model (Prentice, 1976) using a sandwich variance estimator (White, 1982; Zeger et al. 1985) to genetic association studies in which alleles are treated as dependent variables. The validity of switching the positions of allele and trait variables in the regression model is ensured by the invariance property of the odds ratio. The approach is shown to be able to accommodate many commonly seen designs, matched or unmatched alike, having either binary or quantitative traits. The resultant score statistic has potentially higher power than those that have previously appeared in the genetics literature. As a regression model in general, this approach may also be applied to incorporate covariates. Numerical examples implemented with standard software are presented.
本文将使用三明治方差估计量（怀特，1982年；泽格尔等人，1985年）的回顾性逻辑回归模型（普伦蒂斯，1976年）应用于等位基因被视为因变量的基因关联研究。回归模型中等位基因和性状变量位置的互换有效性由优势比的不变性保证。该方法被证明能够适应许多常见的设计，无论是匹配的还是不匹配的，具有二元或定量性状均可。所得的得分统计量可能比遗传学文献中先前出现的那些具有更高的功效。作为一般的回归模型，该方法也可用于纳入协变量。给出了使用标准软件实现的数值示例。
