Analysing panel count data with informative observation times

Chiung Yu Huang, Mei Cheng Wang, Ying Zhang

Research output: Contribution to journalArticle

57 Scopus citations

Abstract

In this paper, we study panel count data with informative observation times. We assume nonparametric and semiparametric proportional rate models for the underlying event process, where the form of the baseline rate function is left unspecified and a subject-specific frailty variable inflates or deflates the rate function multiplicatively. The proposed models allow the event processes and observation times to be correlated through their connections with the unobserved frailty; moreover, the distributions of both the frailty variable and observation times are considered as nuisance parameters. The baseline rate function and the regression parameters are estimated by maximising a conditional likelihood function of observed event counts and solving estimation equations. Large-sample properties of the proposed estimators are studied. Numerical studies demonstrate that the proposed estimation procedures perform well for moderate sample sizes. An application to a bladder tumour study is presented.

Original languageEnglish (US)
Pages (from-to)763-775
Number of pages13
JournalBiometrika
Volume93
Issue number4
DOIs
StatePublished - Dec 1 2006
Externally publishedYes

Keywords

  • Dependent censoring
  • Frailty
  • Poisson process
  • Rate function
  • Serial events

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Agricultural and Biological Sciences(all)
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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