Estimating treatment effect in a proportional hazards model in randomized clinical trials with all-or-nothing compliance.

ABSTRACT: We consider methods for estimating the treatment effect and/or the covariate by treatment interaction effect in a randomized clinical trial under noncompliance with time-to-event outcome. As in Cuzick et al. (2007), assuming that the patient population consists of three (possibly latent) subgroups based on treatment preference: the ambivalent group, the insisters, and the refusers, we estimate the effects among the ambivalent group. The parameters have causal interpretations under standard assumptions. The article contains two main contributions. First, we propose a weighted per-protocol (Wtd PP) estimator through incorporating time-varying weights in a proportional hazards model. In the second part of the article, under the model considered in Cuzick et al. (2007), we propose an EM algori

SUBMITTER: Li S 

PROVIDER: S-EPMC5113714 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature