title: Regression methods for covariate adjustment and subgroup analysis for non-censored cost-effectiveness data.
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.
authors.affiliation: Program in Population Health Sciences, Hospital for Sick Children, and Department of Public Health Services, University of Toronto, ON, Canada. willana@mcmaster.ca
authors.forename: Andrew R
authors.initials: AR
authors.lastname: Willan
authors.forename: Andrew H
authors.initials: AH
authors.lastname: Briggs
authors.forename: Jeffrey S
authors.initials: JS
authors.lastname: Hoch
mesh_terms: D000328:Adult; D002170:Canada; D003362:Cost-Benefit Analysis / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000191:economics* / Q000592:standards / Q000706:statistics & numerical data; D012044:Regression Analysis