Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/43404
Title: Monotone spline-based least squares estimation for panel count data with informative observation times
Authors: Deng, S
Liu, L
Zhao, X 
Keywords: Informative observation process
Least squares estimation
Monotone b-splines
Panel count data
Semiparametric mean models
Issue Date: 2015
Publisher: Wiley-VCH
Source: Biometrical journal, 2015, v. 57, no. 5, p. 743-765 How to cite?
Journal: Biometrical journal 
Abstract: This article discusses the statistical analysis of panel count data when the underlying recurrent event process and observation process may be correlated. For the recurrent event process, we propose a new class of semiparametric mean models that allows for the interaction between the observation history and covariates. For inference on the model parameters, a monotone spline-based least squares estimation approach is developed, and the resulting estimators are consistent and asymptotically normal. In particular, our new approach does not rely on the model specification of the observation process. The proposed inference procedure performs well through simulation studies, and it is illustrated by the analysis of bladder tumor data.
URI: http://hdl.handle.net/10397/43404
ISSN: 0323-3847
EISSN: 1521-4036
DOI: 10.1002/bimj.201400217
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