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Semiparametric Transformation Models with Time‐Varying Coefficients for Recurrent and Terminal Events
Author(s) -
Zhao Xingqiu,
Zhou Jie,
Sun Liuquan
Publication year - 2011
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2010.01458.x
Subject(s) - transformation (genetics) , terminal (telecommunication) , semiparametric model , econometrics , semiparametric regression , statistics , mathematics , computer science , nonparametric statistics , biology , genetics , gene , telecommunications
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.