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Semiparametric analysis of longitudinal data with informative observation times. (English) Zbl 1207.62091
Summary: In many longitudinal studies, observation times as well as censoring times may be correlated with longitudinal responses. This paper considers a multiplicative random effects model for the longitudinal response where these correlations may exist and a joint modeling approach is proposed via a shared latent variable. For inference about regression parameters, estimating equation approaches are developed and asymptotic properties of the proposed estimators are established. The finite sample behavior of the methods is examined through simulation studies and an application to a data set from a bladder cancer study is provided for illustration.

MSC:
62G08 Nonparametric regression and quantile regression
62N02 Estimation in survival analysis and censored data
62N01 Censored data models
62G05 Nonparametric estimation
65C60 Computational problems in statistics (MSC2010)
62P10 Applications of statistics to biology and medical sciences; meta analysis
62G10 Nonparametric hypothesis testing
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