Semiparametric Regression Analysis of Longitudinal Data With Informative Observation Times

Statistical analysis of longitudinal data has been discussed by many authors, and a number of methods have been proposed. Most of the research have focused on situations where observation times are independent of or carry no information about the response variable and therefore rely on conditional i...

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Bibliographic Details
Published in:Journal of the American Statistical Association 2005-09, Vol.100 (471), p.882-889
Main Authors: Sun, Jianguo, Park, Do-Hwan, Sun, Liuquan, Zhao, Xingqiu
Format: Article
Language:English
Subjects:
Consistent estimators
Estimating equation
Estimation bias
Estimation methods
Exact sciences and technology
Inference
Informative observation times
Linear inference, regression
Longitudinal data
Mathematics
Modeling
Nonhomogeneous poisson process
Nonparametric inference
Observational research
Poisson distribution
Probability and statistics
Probability theory and stochastic processes
Regression analysis
School dropouts
Sciences and techniques of general use
Statistical analysis
Statistics
Stochastic processes
Theory and Methods
Tumors
Urinary bladder
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Summary:Statistical analysis of longitudinal data has been discussed by many authors, and a number of methods have been proposed. Most of the research have focused on situations where observation times are independent of or carry no information about the response variable and therefore rely on conditional inference procedures given the observation times. This article considers a different situation, where the independence assumption may not hold; that is, the observation times may carry information about the response variable. For inference, estimating equation approaches are proposed, and both large-sample and final-sample properties of the proposed methods are established. The methodology is applied to a bladder cancer study that motivated this investigation.
ISSN:0162-1459
1537-274X
DOI:10.1198/016214505000000060