Title
The Gamma-Frailty Poisson Model For The Nonparametric Estimation Of Panel Count Data
Keywords
EM algorithm; Isotonic regression; Iterative convex minorant algorithm; Monte-Carlo; Nonparametric maximum pseudo-likelihood estimator
Abstract
In this article, we study nonparametric estimation of the mean function of a counting process with panel observations. We introduce the gamma frailty variable to account for the intracorrelation between the panel counts of the counting process and construct a maximum pseudo- likelihood estimate with the frailty variable. Three simulated examples are given to show that this estimation procedure, while preserving the robustness and simplicity of the computation, improves the efficiency of the nonparametric maximum pseudo-likelihood estimate studied in Wellner and Zhang (2000, Annals of Statistics 28, 779-814). A real example from a bladder tumor study is used to illustrate the method.
Publication Date
12-1-2003
Publication Title
Biometrics
Volume
59
Issue
4
Number of Pages
1099-1106
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1111/j.0006-341X.2003.00126.x
Copyright Status
Unknown
Socpus ID
0346733294 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0346733294
STARS Citation
Zhang, Ying and Jamshidian, Mortaza, "The Gamma-Frailty Poisson Model For The Nonparametric Estimation Of Panel Count Data" (2003). Scopus Export 2000s. 1474.
https://stars.library.ucf.edu/scopus2000/1474