Tchetgen Eric J Tchetgen, Robins James
Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
Biometrics. 2010 Dec;66(4):1138-44. doi: 10.1111/j.1541-0420.2010.01401.x.
We propose a semiparametric case-only estimator of multiplicative gene-environment or gene-gene interactions, under the assumption of conditional independence of the two factors given a vector of potential confounding variables. Our estimator yields valid inferences on the interaction function if either but not necessarily both of two unknown baseline functions of the confounders is correctly modeled. Furthermore, when both models are correct, our estimator has the smallest possible asymptotic variance for estimating the interaction parameter in a semiparametric model that assumes that at least one but not necessarily both baseline models are correct.
我们提出了一种用于估计基因与环境或基因与基因之间乘法相互作用的半参数仅病例估计量,该估计量基于给定潜在混杂变量向量时两个因素的条件独立性假设。如果两个混杂因素的两个未知基线函数中的任意一个(但不一定是两个)被正确建模,我们的估计量就能对相互作用函数进行有效的推断。此外,当两个模型都正确时,在假设至少一个(但不一定是两个)基线模型正确的半参数模型中,我们的估计量在估计相互作用参数时具有尽可能小的渐近方差。