title: Using rank data to estimate health state utility models.
abstract: In this paper we report the estimation of conditional logistic regression models for the Health Utilities Index Mark 2 and the SF-6D, using ordinal preference data. The results are compared to the conventional regression models estimated from standard gamble data, and to the observed mean standard gamble health state valuations. For both the HUI2 and the SF-6D, the models estimated using ordinal data are broadly comparable to the models estimated on standard gamble data and the predictive performance of these models is close to that of the standard gamble models. Our research indicates that ordinal data have the potential to provide useful insights into community health state preferences. However, important questions remain.
authors.affiliation: Health Economics and Decision Science, University of Sheffield, United Kingdom. c.mccabe@sheffield.ac.uk
authors.forename: Christopher
authors.initials: C
authors.lastname: McCabe
authors.forename: John
authors.initials: J
authors.lastname: Brazier
authors.forename: Peter
authors.initials: P
authors.lastname: Gilks
authors.forename: Aki
authors.initials: A
authors.lastname: Tsuchiya
authors.forename: Jennifer
authors.initials: J
authors.lastname: Roberts
authors.forename: Anthony
authors.initials: A
authors.lastname: O'Hagan
authors.forename: Katherine
authors.initials: K
authors.lastname: Stevens
mesh_terms: D006305:Health Status Indicators; D006801:Humans; D015233:Models, Statistical; D006113:United Kingdom / Q000453:epidemiology