Trying to do better than average: a commentary on 'statistical inference for cost-effectiveness ratios'.
In a recent paper, Laska, Meisner and Siegel address issues concerning hypothesis testing in cost-effectiveness analysis. They relate the relative magnitude of two average cost-effectiveness ratios to the incremental cost-effectiveness ratio and go on to propose a statistical procedure for testing the equality of two average ratios. In this paper, we show why the use of average cost-effectiveness ratios is misleading and argue that the appropriate focus for cost-effectiveness analysis is the estimation of confidence intervals around incremental cost-effectiveness ratios.
Briggs
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A
Health Economics Research Centre, University of Oxford, UK.
Fenn
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P
D016001:Confidence Intervals; D003362:Cost-Benefit Analysis / Q000379:methods* / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D006302:Health Services Research / Q000379:methods*; D006801:Humans; D017059:Models, Econometric