Estimation of the Proportional Mean Residual Life Model with Internal and Longitudinal Covariates

Ruiwen Zhou, Jianguo Sun

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The proportional mean residual life model has been discussed by many authors and provides a useful alternative to the commonly used proportional hazards model for regression analysis of failure time data. In this paper, we discuss the estimation of the model when there exist internal and longitudinal covariates or variables in addition to the failure time variable of interest, for which it does not seem to exist an established estimation procedure. For the problem, a joint modeling approach is proposed and in the method, latent variables are used to describe the relationship between the failure time of interest and longitudinal variables. For estimation, a two-step estimation procedure is proposed and the simulation study shows that it works well in practical situations.

Original languageEnglish
Pages (from-to)550-563
Number of pages14
JournalStatistics in Biosciences
Volume14
Issue number3
DOIs
StatePublished - Dec 2022

Keywords

  • Extended estimating equation
  • Joint modeling
  • Mean residual model
  • Proportional model
  • Random effect

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