Semiparametric Transformation Models with Time-Varying Coefficients for Recurrent and Terminal Events

Authors


email:xingqiu.zhao@polyu.edu.hk

email:zhoujie@amss.ac.cn

email:slq@amt.ac.cn

Abstract

Summary In this article, we propose a family of semiparametric transformation models with time-varying coefficients for recurrent event data in the presence of a terminal event such as death. The new model offers great flexibility in formulating the effects of covariates on the mean functions of the recurrent events among survivors at a given time. For the inference on the proposed models, a class of estimating equations is developed and asymptotic properties of the resulting estimators are established. In addition, a lack-of-fit test is provided for assessing the adequacy of the model, and some tests are presented for investigating whether or not covariate effects vary with time. The finite-sample behavior of the proposed methods is examined through Monte Carlo simulation studies, and an application to a bladder cancer study is also illustrated.

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