Regression methods for covariate adjustment and subgroup analysis for non-censored cost-effectiveness data

Andrew R. Willan, Andrew H. Briggs, Jeffrey S Hoch

Research output: Contribution to journalArticle

163 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)461-475
Number of pages15
JournalHealth Economics
Volume13
Issue number5
DOIs
StatePublished - May 2004
Externally publishedYes

Keywords

  • Clinical trials
  • Cost-effectiveness analysis
  • Covariate adjustment
  • Regression

ASJC Scopus subject areas

  • Nursing(all)
  • Economics and Econometrics
  • Health(social science)
  • Health Professions(all)

Fingerprint Dive into the research topics of 'Regression methods for covariate adjustment and subgroup analysis for non-censored cost-effectiveness data'. Together they form a unique fingerprint.

  • Cite this