Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14667
Title: Semiparametric regression analysis of panel count data with informative observation times
Authors: Zhao, X 
Tong, X
Keywords: Estimating equation
Informative observation times
Mean function model
Panel count data
Regression analysis
Issue Date: 2011
Publisher: Elsevier Science Bv
Source: Computational statistics and data analysis, 2011, v. 55, no. 1, p. 291-300 How to cite?
Journal: Computational Statistics and Data Analysis 
Abstract: This paper discusses regression analysis of panel count data that arise naturally when recurrent events are considered. For the analysis of panel count data, most of the existing methods have assumed that observation times are completely independent of recurrent events or given covariates, which may not be true in practice. We propose a joint modeling approach that uses an unobserved random variable and a completely unspecified link function to characterize the correlations between the response variable and the observation times. For inference about regression parameters, estimating equation approaches are developed without involving any estimation for latent variables, and the asymptotic properties of the resulting estimators are established. In addition, a technique is provided for assessing the adequacy of the model. The performance of the proposed estimation procedures are evaluated by means of Monte Carlo simulations, and a data set from a bladder tumor study is analyzed as an illustrative example.
URI: http://hdl.handle.net/10397/14667
DOI: 10.1016/j.csda.2010.04.020
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