Abstract
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 language | English (US) |
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Pages (from-to) | 1533-1546 |
Number of pages | 14 |
Journal | Statistics in Medicine |
Volume | 25 |
Issue number | 9 |
DOIs | |
State | Published - May 15 2006 |
Keywords
- Bayesian inference
- Clinical trial
- Importance sampling
- Multiple imputation
ASJC Scopus subject areas
- Epidemiology
- Statistics and Probability