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SCIENCE CHINA Mathematics, Volume 59, Issue 12: 2393-2410(2016) https://doi.org/10.1007/s11425-016-0112-6

Time-varying latent model for longitudinal data with informative observation and terminal event times

More info
  • ReceivedFeb 19, 2016
  • AcceptedOct 10, 2016
  • PublishedOct 31, 2016

Abstract

Longitudinal data often occur in follow-up studies, and in many situations, there may exist informative observation times and a dependent terminal event such as death that stops the follow-up. We propose a semiparametric mixed effect model with time-varying latent effects in the analysis of longitudinal data with informative observation times and a dependent terminal event. Estimating equation approaches are developed for parameter estimation, and asymptotic properties of the resulting estimators are established. The finite sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a bladder cancer study is provided.


Funded by

Key Laboratory of Random Complex Structures and Data Science Chinese Academy of Sciences(2008DP173182)

National Natural Science Foundation of China(11231010)

National Natural Science Foundation of China(11201315)

National Natural Science Foundation of China(11171330)


Acknowledgment

Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant Nos. 11231010, 11171330 and 11201315), Key Laboratory of Random Complex Structures and Data Science, Chinese Academy of Sciences (Grant No. 2008DP173182) and Beijing Center for Mathematics and Information Interdisciplinary Sciences. The authors thank the associate editor-in-chief, the associate editor and the two reviewers for their constructive and insightful comments and suggestions that greatly improved the paper.


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