O'Hagan A, Stevens J W, Montmartin J
Statistical Services Unit, University of Sheffield, South Yorkshire, England.
Pharmacoeconomics. 2000 Apr;17(4):339-49. doi: 10.2165/00019053-200017040-00004.
The aim of this article is to consider Bayesian and frequentist inference methods for measures of incremental cost effectiveness in data obtained via a clinical trial. The most useful measure is the cost-effectiveness (C/E) acceptability curve. Recent publications on Bayesian estimation have assumed a normal posterior distribution, which ignores uncertainty in estimated variances, and suggest unnecessarily complicated methods of computation. We present a simple Bayesian computation for the C/E acceptability curve and a simple frequentist analogue. Our approach takes account of errors in estimated variances, resulting in calculations that are based on distributions rather than normal distributions. If inference is required about the C/E ratio, we argue that the standard frequentist procedures give unreliable or misleading inferences, and present instead a Bayesian interval.
本文旨在探讨在通过临床试验获得的数据中，用于增量成本效益度量的贝叶斯推断方法和频率论推断方法。最有用的度量是成本效益（C/E）可接受性曲线。近期关于贝叶斯估计的出版物假设后验分布为正态分布，这忽略了估计方差中的不确定性，并提出了不必要的复杂计算方法。我们提出了一种用于C/E可接受性曲线的简单贝叶斯计算方法以及一种简单的频率论类似方法。我们的方法考虑了估计方差中的误差，从而得出基于分布而非正态分布的计算结果。如果需要对C/E比率进行推断，我们认为标准的频率论程序会给出不可靠或误导性的推断，因此我们提出了一个贝叶斯区间。
