Semiparametric Transformation Models with Time‐Varying Coefficients for Recurrent and Terminal Events |
| |
Authors: | Xingqiu Zhao Jie Zhou Liuquan Sun |
| |
Affiliation: | 1. Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China;2. Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing 100190, China |
| |
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. |
| |
Keywords: | Counting process Estimating equation Marginal model Model checking Recurrent events Terminal event Time‐varying coefficients |
|
|