Lifetime Data Anal - Robust inference in discrete hazard models for randomized clinical trials.

Tópicos

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Resumo

Time-to-event data in which failures are only assessed at discrete time points are common in many clinical trials. Examples include oncology studies where events are observed through periodic screenings such as radiographic scans. When the survival endpoint is acknowledged to be discrete, common methods for the analysis of observed failure times include the discrete hazard models (e.g., the discrete-time proportional hazards and the continuation ratio model) and the proportional odds model. In this manuscript, we consider estimation of a marginal treatment effect in discrete hazard models where the constant treatment effect assumption is violated. We demonstrate that the estimator resulting from these discrete hazard models is consistent for a parameter that depends on the underlying censoring distribution. An estimator that removes the dependence on the censoring mechanism is proposed and its asymptotic distribution is derived. Basing inference on the proposed estimator allows for statistical inference that is scientifically meaningful and reproducible. Simulation is used to assess the performance of the presented methodology in finite samples.

Resumo Limpo

timetoev data failur assess discret time point common mani clinic trial exampl includ oncolog studi event observ period screen radiograph scan surviv endpoint acknowledg discret common method analysi observ failur time includ discret hazard model eg discretetim proport hazard continu ratio model proport odd model manuscript consid estim margin treatment effect discret hazard model constant treatment effect assumpt violat demonstr estim result discret hazard model consist paramet depend under censor distribut estim remov depend censor mechan propos asymptot distribut deriv base infer propos estim allow statist infer scientif meaning reproduc simul use assess perform present methodolog finit sampl

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