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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.||URI:||http://hdl.handle.net/123456789/758|
|Appears in Programs:||0480 Statistics & Operations Research|
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