A multiparameter regression model for interval-censored survival data

Defen Peng, Gilbert MacKenzie, Kevin Burke

Research output: Contribution to journalArticlepeer-review

Abstract

We develop flexible multiparameter regression (MPR) survival models for interval-censored survival data arising in longitudinal prospective studies and longitudinal randomised controlled clinical trials. A multiparameter Weibull regression survival model, which is wholly parametric, and has nonproportional hazards, is the main focus of the article. We describe the basic model, develop the interval-censored likelihood, and extend the model to include gamma frailty and a dispersion model. We evaluate the models by means of a simulation study and a detailed reanalysis of data from the Signal Tandmobiel study. The results demonstrate that the MPR model with frailty is computationally efficient and provides an excellent fit to the data.

Original languageEnglish
Pages (from-to)1903-1918
Number of pages16
JournalStatistics in Medicine
Volume39
Issue number14
DOIs
Publication statusPublished - 30 Jun 2020

Keywords

  • crossing hazards
  • dispersion model
  • gamma frailty
  • interval censoring
  • longitudinal studies
  • multiparameter regression survival models
  • nonproportional hazards Weibull

Fingerprint

Dive into the research topics of 'A multiparameter regression model for interval-censored survival data'. Together they form a unique fingerprint.

Cite this