The Gamma-Frailty Poisson Model for the Nonparametric Estimation of Panel Count Data

Ying Zhang, Mortaza Jamshidian

Research output: Contribution to journalArticle

14 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1099-1106
Number of pages8
JournalBiometrics
Volume59
Issue number4
DOIs
StatePublished - Dec 1 2003
Externally publishedYes

Keywords

  • EM algorithm
  • Isotonic regression
  • Iterative convex minorant algorithm
  • Monte-Carlo
  • Nonparametric maximum pseudo-likelihood estimator

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Fingerprint Dive into the research topics of 'The Gamma-Frailty Poisson Model for the Nonparametric Estimation of Panel Count Data'. Together they form a unique fingerprint.

  • Cite this