Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/48498
Título: Using covariates to reduce uncertainty in the economic evaluation of clinical trial data
Autores/as: Vázquez Polo, Francisco José 
Negrín Hernández, Miguel Ángel 
González Lopez-Valcarcel, Beatriz 
Clasificación UNESCO: 531207 Sanidad
Palabras clave: Economía de la salud
Modelos económetricos
Fecha de publicación: 2005
Editor/a: 1057-9230
Publicación seriada: Health Economics 
Resumen: As part of their practice, policymakers have to make economic evaluations using clinical trial data. Recent interest has been expressed in determining how cost-effectiveness analysis can be undertaken in a regression framework. In this respect, published research basically provides a general method for prognostic factor adjustment in the presence of imbalance, emphasizing sub-group analysis. In this paper, we present an alternative method from a Bayesian approach. We propose the use of covariates in Bayesian health technology assessment in order to reduce uncertainty about the effect of treatments. We show its advantages by comparison with another published method that do not adjust for covariates using simulated data.
URI: http://hdl.handle.net/10553/48498
ISSN: 1057-9230
DOI: 10.1002/hec.947
Fuente: Health Economics[ISSN 1057-9230],v. 14, p. 545-557
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