Robust estimation of multivariate failure data with time-modulated frailty

Pingfu Fu, J. Sunil Rao, Jiming Jiang

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

A time-modulated frailty model is proposed for analyzing multivariate failure data. The effect of frailties, which may not be constant over time, is discussed. We assume a parametric model for the baseline hazard, but avoid the parametric assumption for the frailty distribution. The well-known connection between survival times and Poisson regression model is used. The parameters of interest are estimated by generalized estimating equations (GEE) or by penalized GEE. Simulation studies show that the procedure is successful to detect the effect of time-modulated frailty. The method is also applied to a placebo controlled randomized clinical trial of gamma interferon, a study of chronic granulomatous disease (CGD).

Original languageEnglish (US)
Pages (from-to)367-378
Number of pages12
JournalJournal of Modern Applied Statistical Methods
Volume1
Issue number2
DOIs
StatePublished - Jan 1 2002
Externally publishedYes

Keywords

  • Frailty models
  • Generalized linear models
  • Multivariate failure data

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

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