On the Exact Interval Estimation for the Many-to-One Comparison in the Probability of Cost-Effectiveness

• Activity Number: 269
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Health Policy Statistics Section
• Author(s): Chi-Rong Li* and Tsai-Yu Lin
• Companies: Chung Shan Medical University and Feng Chia University
• Keywords: generalized confidence interval ; nonparametric method ; many-to-one comparison ; skewness ; area under the ROC curve

Abstract

In health economics, public health and health science, the cost-effectiveness analysis is a type of economic evaluation that examines the costs-effectiveness of two competing treatments or interventions. However limited statistical approaches have been developed for the evaluation comparing more than two treatments. The probability of cost-effectiveness is an measure, which expresses the chance of gaining net benefit based on the probability distribution of cost-effectiveness ratio. Unlike the incremental cost-effectiveness ratio (ICER) and its derivative measures that are constructed by mean cost and mean effectiveness, the probability of cost-effectiveness is not sensitive to extreme value. In this study we propose to use the concept of generalized pivotal quantities to construct an exact interval estimation for the many-to-one comparison (several experimental treatments are compared with a control treatment) in the probability of cost-effectiveness. Simulation results demonstrate that our proposed interval estimation provides not only sufficient probability coverage but reasonable expected length. Numerical examples using published data sets of illustrate the proposed method.