Ewell M
EMMES Corporation, Potomac, Maryland 20854, USA.
Stat Med. 1996;15(21-22):2379-92. doi: 10.1002/(SICI)1097-0258(19961115)15:21<2379::AID-SIM457>3.0.CO;2-L.
A method is introduced for computing a Bayesian 95 per cent posterior probability region for vaccine efficacy. This method assumes independent vague gamma prior distributions for the incidence rates on each arm of the trial, and a Poisson likelihood for the counts of incident cases of infection. The approach is similar in spirit to the Bayesian analysis of the binomial risk ratio described by Aitchison and Bacon-Shone. However, the focus of our interest is not on incorporating prior information into the design of trials for efficacy, but rather on evaluating whether or not the Bayesian approach with vague prior information produces comparable results to a frequentist approach. A review of methods for constructing exact and large sample intervals for vaccine efficacy is provided as a framework for comparison. The confidence interval methods are assessed by comparing the size and power of tests of vaccine efficacy in proposed intermediate sized randomized double blinded placebo controlled trials.
本文介绍了一种计算疫苗效力的贝叶斯95%后验概率区域的方法。该方法假定试验各臂上的发病率服从独立的模糊伽马先验分布，且感染病例数服从泊松似然分布。这种方法在本质上与艾奇逊和培根-肖恩所描述的二项风险比的贝叶斯分析相似。然而，我们感兴趣的重点不是将先验信息纳入效力试验的设计中，而是评估具有模糊先验信息的贝叶斯方法是否能产生与频率论方法可比的结果。作为比较框架，本文提供了关于构建疫苗效力精确和大样本区间方法的综述。通过比较拟议的中等规模随机双盲安慰剂对照试验中疫苗效力检验的大小和功效，对置信区间方法进行了评估。
