White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

Tails from the Peak District: adjusted censored mixture models of EQ-5D health state utility values

Hernández Alava, M., Wailoo, A.J. and Ara, R. (2010) Tails from the Peak District: adjusted censored mixture models of EQ-5D health state utility values. Discussion Paper. (Unpublished)


There is a more recent version of this eprint available. Click here to view it.

[img] Text

Download (347Kb)
[img] Other

Download (15Kb)


Health state utility data generated using the EQ-5D instrument are typically right bounded at one with a substantial gap to the next set of observations, left bounded by some negative value, and are multi modal. These features present challenges to the estimation of the e¤ect of clinical and socioeconomic characteristics on health utilities. We present an adjusted censored model and then use this in a flexible, mixture modelling framework to address these issues. We demonstrate superior performance of this model compared to linear regression and Tobit censored regression using a dataset from repeated observations of patients with rheumatoid arthritis. We �nd that three latent classes are appropriate in estimating EQ-5D from function, pain and sociodemographic factors. Analysis of utility data should apply methods that recognise the distributional features of the data.

Item Type: Monograph (Discussion Paper)
Keywords: Mixture models, latent class model, censored regression, EQ-5D, mapping
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > Health Economics and Decision Science > HEDS Discussion Paper Series
Depositing User: ScHARR / HEDS (Sheffield)
Date Deposited: 04 Aug 2010 08:26
Last Modified: 04 Jun 2014 11:51
Status: Unpublished
Identification Number: HEDS Discussion Paper 10/08
URI: http://eprints.whiterose.ac.uk/id/eprint/11074

Available Versions of this Item

Actions (repository staff only: login required)