Multivariate survival data under bivariate frailty: An estimating equation approach

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

A modified frailty model is developed to improve the computing efficiency of the bivariate frailty model proposed by Xue and Brookmeyer (1996, Lifetime Data Analysis 2, 277-290) for the analysis of multivariate survival data. Originally, the frailty was modeled parametrically and a modified EM approach was used to estimate the parameters of interest, however, with intensive computations. The modified frailty model formulates a Poisson regression model and applies quasi-likelihood estimating equations to estimate the parameters of interest. This procedure not only significantly reduces the computation but also avoids using a parametric assumption for the frailty distribution. Simulation studies show the estimators perform well. The method is also applied to a mental health care dataset.

Original languageEnglish (US)
Pages (from-to)1631-1637
Number of pages7
JournalBiometrics
Volume54
Issue number4
DOIs
StatePublished - 1998
Externally publishedYes

Fingerprint

Multivariate Survival Data
Frailty Model
Frailty
Estimating Equation
Survival Analysis
Lifetime Data
Poisson Regression
Mental Health
Quasi-likelihood
Multivariate Analysis
Poisson Model
Delivery of Health Care
Estimate
Healthcare
mental health
Regression Model
Data analysis
Health care
Simulation Study
health services

Keywords

  • Heterogeneity
  • Poisson formulation
  • Quasi-likelihood

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Public Health, Environmental and Occupational Health
  • Agricultural and Biological Sciences (miscellaneous)
  • Applied Mathematics
  • Statistics and Probability

Cite this

Multivariate survival data under bivariate frailty : An estimating equation approach. / Xue, Xiaonan (Nan).

In: Biometrics, Vol. 54, No. 4, 1998, p. 1631-1637.

Research output: Contribution to journalArticle

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