Causal Inference in a Placebo-Controlled Clinical Trial With Binary Outcome and Ordered Compliance
提出一种基于似然的方法，分析部分依从性（即未按计划完全接受治疗或安慰剂）的因果效应，利用LRC-CPPT数据估计不同依从性亚组的暴露-反应曲线，并讨论方法的适用性和扩展。
Abstract We propose a likelihood-based method to analyze the causal effect of partial compliance (i.e., unplanned partial exposure to treatment or placebo) in the LRC-CPPT data, a prevention trial with long term follow-up previously analyzed by Efron and Feldman. Initially, we construct ordered compliance categories and dichotomize response. Assuming increased exposure to cholestyramine does not increase cholesterol, we estimate exposure—response curves in different compliance subsets. Subjects in different arms with similar levels of compliance to the assignment may have a different placebo prognosis (i.e., success probability under a possible zero exposure level). The sole assumption that the placebo group reflects response to zero exposure for the treatment group as a whole allows estimation of a causal parameter in a special case only. When a single parameter represents the association between responses to possible treatment exposures and treatment compliance, simple estimates are derived for a set of causal parameters. The example is analyzed in detail, and more general applicability and extensions of the method are discussed.