Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32289
Title: Nonparametric inference based on panel count data
Authors: Zhao, X 
Balakrishnan, N
Sun, J
Keywords: Bayesian estimation
Generalized least-squares
Markov model
Mean function
Nonparametric comparison
Nonparametric maximum likelihood
Nonparametric maximum pseudo-likelihood
Panel count data
Rate function
Issue Date: 2011
Publisher: Springer
Source: Test, 2011, v. 20, no. 1, p. 1-42 How to cite?
Journal: Test 
Abstract: Panel count data usually refer to data arising from studies on recurrent events in which the subjects under study are followed or observed only periodically rather than continuously. In such situations, an objective of interest is about the occurrence of some events that can occur multiple times or repeatedly and the studies resulting in this type of information are often referred to as event history studies. There are many fields such as medical studies, reliability experiments and social sciences wherein panel count data are encountered commonly. This article reviews basic concepts about panel count data, some common issues and questions of interest regarding them as well as the corresponding statistical procedures that are suitable for their analysis. In particular, we will discuss an estimation of the mean function of the underlying counting process characterizing the occurrence of the events, comparison of several processes and analysis of multiple state panel count data. Some discussion is also presented of situations involving dependent or informative observation processes.
URI: http://hdl.handle.net/10397/32289
DOI: 10.1007/s11749-010-0223-1
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