A pattern-mixture model for the analysis of censored quality-of-life data

Huiling Li, Daniel F. Heitjan

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


We propose a pattern-mixture model for describing the joint distribution of incomplete repeated measurements of quality of life (QoL) and right-censored survival times. The model assumes that the survival times follow a multinomial distribution and that the quality of life outcome follows a multivariate normal distribution conditional on the survival time. We estimate the model using a Bayesian approach by importance sampling. We then use simulated parameters to create multiple imputations of the censored QoL outcomes, which can then be used to calculate individual values of quality-adjusted life-years (QALYs). We apply the method to data from the Randomized Evaluation of Mechanical Assistance in the Treatment of Congestive Heart Failure (REMATCH) clinical trial.

Original languageEnglish (US)
Pages (from-to)1533-1546
Number of pages14
JournalStatistics in Medicine
Issue number9
StatePublished - May 15 2006


  • Bayesian inference
  • Clinical trial
  • Importance sampling
  • Multiple imputation

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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