University of Sheffield

Tony O'Hagan - Academic pages - Abstracts


Assessing and Comparing Costs: How Robust are the Bootstrap and Methods Based on Asymptotic Normality?

Anthony O'Hagan and John W. Stevens

Statistical Services Unit, University of Sheffield, Sheffield, England and Astra Charnwood, Loughborough, England

Publication details: Health Economics, 12, 33-49, 2003.


This article addresses and challenges some common perceptions in the statistical assessment of costs and cost-effectiveness in health economics. Cost data typically exhibit highly skew distributions. Two techniques whose validity does not depend on any specific form of underlying distribution are the bootstrap and methods based on asymptotic normality of sample means. These methods are generally thought to be appropriate for the analysis of cost data.

We argue that, even when these methods are technically valid, they may often lead to inefficient and even misleading inferences. It is important to apply methods that recognise the skewness in cost data.

We further demonstrate that it may also be important to incorporate relevant prior information in a Bayesian analysis.

Keywords: Bayesian statistics; Bootstrap; Cost-effectiveness; Dirichlet process; Nonparametric methods; Normal-theory methods; Pharmacoeconomics; Robustness.

Return to my publications page.
Updated: 18 December 2002
Maintained by: Tony O'Hagan