title: Who's better not best: appropriate probabilistic uncertainty analysis.
abstract: The use of probabilistic analysis as a means for analyzing uncertainty within economic analysis has grown in popularity in recent years as it has been recognized as the most complete method for propagating uncertainty with respect to input parameters in terms of uncertainty about outcomes of interest. The World Health Organization (WHO) in a series of recent reports and publications have recognized the role of probabilistic analysis in what they term generalized cost-effectiveness analysis. However, there are fundamental problems with the analysis and the interpretation of such analysis as proposed by WHO. This study highlights three specific points for concern and offers constructive criticism by recommending more appropriate approaches.
authors.affiliation: Clinical Epidemiology Unit, Ottawa Health Research Institute, Ottawa Hospital, Ontario, Canada. dcoyle@ohri.ca
authors.forename: Douglas
authors.initials: D
authors.lastname: Coyle
mesh_terms: D002170:Canada; D016001:Confidence Intervals; D003362:Cost-Benefit Analysis / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D006302:Health Services Research / Q000379:methods*; D017059:Models, Econometric; D009010:Monte Carlo Method; D011336:Probability; D013269:Stochastic Processes; D035501:Uncertainty; D014944:World Health Organization