Regression analysis of longitudinal data with time-dependent covariates in the presence of informative observation and censoring times |
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Authors: | Liuquan Sun Xinyuan Song |
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Affiliation: | a Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, PR China b Department of Statistics, The Chinese University of Hong Kong, Hong Kong, PR China |
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Abstract: | In longitudinal observational studies, repeated measures are often correlated with observation times as well as censoring time. This article proposes joint modeling and analysis of longitudinal data with time-dependent covariates in the presence of informative observation and censoring times via a latent variable. Estimating equation approaches are developed for parameter estimation and asymptotic properties of the proposed estimators are established. In addition, a generalization of the semiparametric model with time-varying coefficients for the longitudinal response is considered. Furthermore, 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 in simulation studies, and an application to a bladder cancer study is illustrated. |
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Keywords: | Generalized estimating equations Informative observation times Joint modeling Latent variables Model checking Time-varying coefficient |
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