Abstract
In health policy and economics studies, the incremental cost-effectiveness ratio (ICER) has long been used to compare the economic consequences relative to the health benefits of therapies. Due to the skewed distributions of the costs and ICERs, much research has been done on how to obtain confidence intervals of ICERs, using either parametric or nonparametric methods, with or without the presence of censoring. In this paper, we will examine and compare the finite sample performance of many approaches via simulation studies. For the special situation when the health effect of the treatment is not statistically significant, we will propose a new bootstrapping approach to improve upon the bootstrap percentile method that is currently available. The most efficient way of constructing confidence intervals will be identified and extended to the censored data case. Finally, a data example from a cardiovascular clinical trial is used to demonstrate the application of these methods.
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