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Title: Modelling SF-6D Health State Preference Data using Bayesian
Authors: Wadha Ahmad Jassim Shumais 
Supervisor: Prof. Fahimah Al-Awadhi
Keywords: Modelling SF-6D Health State , Data using Bayesian , Random Effect Model
Issue Date: 2018
Publisher:  Kuwait university - college of graduate studies
Abstract: The thesis presents an approach to modelling SF-6D health states preference data. It provides a new approach to estimating health state values data using Bayesian methods. The data set is the UK 6-dimensional short form health survey (SF-6D) valuation study, which is a generic preference-based measure of health derivative from the 36-item short form health survey (SF-36). A sample of 249 health states defined by the SF-6D was valued by a representative sample of 611 members of the UK general population, using the standard gamble (SG). The thesis presents the results from applying two random effect models to the data using a Bayesian approach; one with constant variance and another with variable variance, and then comparing these results to the original results of the random effect model estimated using a classical approach. The thesis also investigates these results for the future implementation of the SF- 6D and further work in the field.
Appears in Programs:0480 Statistics & Operations Research

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