Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/47677
Título: Eliciting expert opinion for cost-effectiveness analysis: a flexible family of prior distributions
Autores/as: Martel Escobar, María Carmen 
Negrín Hernández, Miguel Ángel 
Vázquez Polo, Francisco José 
Clasificación UNESCO: 530204 Estadística económica
Palabras clave: Estadística bayesiana
Análisis coste-beneficio
Fecha de publicación: 2009
Editor/a: 1696-2281
Publicación seriada: SORT 
Resumen: The Bayesian approach to statistics has been growing rapidly in popularity as an alternative to the classical approach in the economic evaluation of health technologies, due to the significant benefits it affords. One of the most important advantages of Bayesian methods is their incorporation of prior information. Thus, use is made of a greater amount of information, and so stronger results are obtained than with frequentist methods. However, since Stevens and O'Hagan (2002) showed that the elicitation of a prior distribution on the parameters of interest plays a crucial role in a Bayesian cost-effectiveness analysis, relatively few papers have addressed this issue. In a cost-effectiveness analysis, the parameters of interest are the mean efficacy and mean cost of each treatment. The most common prior structure for these two parameters is the bivariate normal structure. In this paper, we study the use of a more general (and flexible) family of prior distributions for the parameters. In particular, we assume that the conditional densities of the parameters are all normal. The model is validated using data of a real clinical trial. The posterior distributions have been simulated using Markov Chain Monte Carlo techniques.
URI: http://hdl.handle.net/10553/47677
ISSN: 1696-2281
Fuente: SORT[ISSN 1696-2281],v. 33, p. 193-211
Colección:Artículos
miniatura
Adobe PDF (219,29 kB)
Vista completa

Citas SCOPUSTM   

1
actualizado el 24-mar-2024

Visitas

33
actualizado el 28-ene-2023

Descargas

9
actualizado el 28-ene-2023

Google ScholarTM

Verifica


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.