Nonparametric inference based on panel count data

Xingqiu Zhao, N. Balakrishnan, Jianguo Sun

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)1-42
Number of pages42
JournalTest
Volume20
Issue number1
DOIs
Publication statusPublished - 1 May 2011

Keywords

  • Bayesian estimation
  • Generalized least-squares
  • Markov model
  • Mean function
  • Nonparametric comparison
  • Nonparametric maximum likelihood
  • Nonparametric maximum pseudo-likelihood
  • Panel count data
  • Rate function

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this