On Modeling and Estimation for the Relative Risk and Risk Difference

A common problem in formulating models for the relative risk and risk difference is the variation dependence between these parameters and the baseline risk, which is a nuisance model. We address this problem by proposing the conditional log odds-product as a preferred nuisance model. This novel nuisance model facilitates maximum-likelihood estimation, but also permits doubly-robust estimation for the parameters of interest. Our approach is illustrated via simulations and a data analysis. An R package implementing the proposed methods is available on CRAN. Supplementary materials for this article are available online.

在构建相对风险（relative risk）与风险差（risk difference）的模型过程中，一类常见问题在于这两类参数与基线风险（baseline risk）之间存在变异性依赖，此类依赖属于讨厌参数模型（nuisance model）范畴。针对该问题，本文提出将条件对数优势积（conditional log odds-product）作为优选的讨厌参数模型。这一新颖的讨厌参数模型不仅可支持最大似然估计（maximum-likelihood estimation），还能针对目标参数实现双重稳健估计（doubly-robust estimation）。本文通过模拟实验与实例数据分析对所提方法进行了演示验证，配套的R软件包已在CRAN上发布，本文的补充材料可在线获取。