The effect of outliers on confidence interval procedures for cost-effectiveness ratios

Cost-effectiveness ratio (CER) is defined as the ratio of the difference in cost between a test and standard health care programme to the difference in benefit, respectively. Methods to obtain confidence intervals for CERs are either variants of Fieller's method (1954), or bootstrap methods. We study the effect of outliers in cost measures on the precision of confidence interval procedures for CERs. In particular the performance of the procedures under single and multiple case influential deletion diagnostics, respectively, are evaluated. Simulation studies suggest that the bias-corrected percentile bootstrap procedure gives better precision and coverage under either diagnostic.