Inference for the cost-effectiveness acceptability curve and cost-effectiveness ratio.
The aim of this article is to consider Bayesian and frequentist inference methods for measures of incremental cost effectiveness in data obtained via a clinical trial. The most useful measure is the cost-effectiveness (C/E) acceptability curve. Recent publications on Bayesian estimation have assumed a normal posterior distribution, which ignores uncertainty in estimated variances, and suggest unnecessarily complicated methods of computation. We present a simple Bayesian computation for the C/E acceptability curve and a simple frequentist analogue. Our approach takes account of errors in estimated variances, resulting in calculations that are based on distributions rather than normal distributions. If inference is required about the C/E ratio, we argue that the standard frequentist procedures give unreliable or misleading inferences, and present instead a Bayesian interval.
O'Hagan
A
A
Statistical Services Unit, University of Sheffield, South Yorkshire, England. a.ohagan@sheffield.ac.uk
Stevens
J W
JW
Montmartin
J
J
D018501:Antirheumatic Agents / Q000191:economics / Q000627:therapeutic use; D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000191:economics; D003362:Cost-Benefit Analysis; D006801:Humans; D053590:Interleukin 1 Receptor Antagonist Protein; D012795:Sialoglycoproteins / Q000191:economics / Q000627:therapeutic use; D015996:Survival Rate; D018746:Systemic Inflammatory Response Syndrome / Q000188:drug therapy / Q000191:economics / Q000401:mortality
D018501:Antirheumatic Agents; C507763:IL1RN protein, human; D053590:Interleukin 1 Receptor Antagonist Protein; D012795:Sialoglycoproteins