title: Average cost-effectiveness ratio with censored data.
abstract: In cost-effectiveness analysis, interest could lie foremost in the incremental cost-effectiveness ratio (ICER), which is the ratio of the incremental cost to the incremental benefit of two competing interventions. The average cost-effectiveness ratio (ACER) is the ratio of the cost to benefit of an intervention without reference to a comparator. A vast literature is available for statistical inference of the ICERs, but limited methods have been developed for the ACERs, particularly in the presence of censoring. Censoring is a common feature in prospective studies, and valid analyses should properly adjust for censoring in cost as well as in effectiveness. In this article, we propose statistical methods for constructing a confidence interval for the ACER from censored data. Different methods-Fieller, Taylor, bootstrap-are proposed, and through simulation studies and data analysis, we address the performance characteristics of these methods.
authors.affiliation: Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, California, USA. hbang@ucdavis.edu
authors.forename: Heejung
authors.initials: H
authors.lastname: Bang
authors.forename: Hongwei
authors.initials: H
authors.lastname: Zhao
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016001:Confidence Intervals; D003362:Cost-Benefit Analysis / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D011446:Prospective Studies