JSM 2004 - Toronto

Abstract #300643

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Activity Number: 397
Type: Topic Contributed
Date/Time: Thursday, August 12, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #300643
Title: Analysis of Incomplete HRQoL Data in the REMATCH Trial
Author(s): Huiling Li*+ and Daniel F. Heitjan
Companies: Columbia University and University of Pennsylvania
Address: 100 Haven Ave., Apt 26G, New York, NY, 10032,
Keywords: Bayesian inference ; clinical trials ; importance sampling ; multiple imputation ; pattern-mixture model
Abstract:

A pattern-mixture model is applied for modeling the joint distribution of incomplete repeated measurements of quality of life and right-censored survival times in the evaluation of how a treatment affects an individual's well-being over time. The statistical model assumes that the survival times follow a multinomial distribution and that quality-of-life outcomes follow a multivariate normal distribution conditional on the survival time. The model is estimated using a Bayesian approach by importance sampling, and then used to create multiple imputation of the missing outcomes. The methods are illustrated through the analysis of the data from a randomized clinical trial of a treatment for cardiovascular disease.

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