Statistical Models for Quality of Life Measures

Yuko Y. Palesch and Alan J. Gross
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Yuko Y. Palesch: Medical University of South Carolina
Alan J. Gross: Medical University of South Carolina

A chapter in Lifetime Data: Models in Reliability and Survival Analysis, 1996, pp 251-255 from Springer

Abstract: Abstract Quality of life (QOL) measures are becoming an integral part of the analysis of clinical trials data to determine the efficacy of interventions. A brief overview of the QOL measures and their corresponding methods of analysis is presented. Then, we propose a statistical model for a discrete QOL measure based on a first order homogeneous Markov process. Heuristically, the model incorporates covariates and allows for nonignorable censoring. Using the model, the efficacy of an intervention can be evaluated by comparing among the treatment groups the expected length of stay in the “good” QOL state in conjunction with the analysis of survival time.

Keywords: Markov Chain Model; Global Index; Sickness Impact Profile; Accelerate Failure Time Model; Quality Adjusted Survival (search for similar items in EconPapers)
Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4757-5654-8_33

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DOI: 10.1007/978-1-4757-5654-8_33

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