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Regression analysis of longitudinal data with time-dependent covariates in the presence of informative observation and censoring times. (English) Zbl 1213.62072
Summary: In longitudinal observational studies, repeated measures are often correlated with observation times as well as censoring times. This article proposes joint modeling and analysis of longitudinal data with time-dependent covariates in the presence of informative observations 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.

MSC:
62G08 Nonparametric regression and quantile regression
62N01 Censored data models
62N02 Estimation in survival analysis and censored data
62F12 Asymptotic properties of parametric estimators
65C60 Computational problems in statistics (MSC2010)
62P10 Applications of statistics to biology and medical sciences; meta analysis
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