Regression methods for covariate adjustment and subgroup analysis for non‐censored cost‐effectiveness data
Andrew R. Willan,
Andrew H. Briggs and
Jeffrey Hoch
Health Economics, 2004, vol. 13, issue 5, 461-475
Abstract:
The current interest in undertaking cost‐effectiveness analyses alongside clinical trials has lead to the increasing availability of patient‐level data on both the costs and effectiveness of intervention. In a recent paper, we show how cost‐effectiveness analysis can be undertaken in a regression framework. In the current paper we develop a direct regression approach to cost‐effectiveness analysis by proposing the use of a system of seemingly unrelated regression equations to provide a more general method for prognostic factor adjustment with emphasis on sub‐group analysis. This more general method can be used in either an incremental cost‐effectiveness or an incremental net‐benefit approach, and does not require that the set of independent variables for costs and effectiveness be the same. Furthermore, the method can exhibit efficiency gains over unrelated ordinary least squares regression. Copyright © 2003 John Wiley & Sons, Ltd.
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (36)
Downloads: (external link)
https://doi.org/10.1002/hec.843
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:hlthec:v:13:y:2004:i:5:p:461-475
Access Statistics for this article
Health Economics is currently edited by Alan Maynard, John Hutton and Andrew Jones
More articles in Health Economics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().