Eddy D M, Hasselblad V, Shachter R
Duke University.
Int J Technol Assess Health Care. 1990;6(1):31-55. doi: 10.1017/s0266462300008928.
This article describes a collection of meta-analysis techniques based on Bayesian statistics for interpreting, adjusting, and combining evidence to estimate parameters and outcomes important to the assessment of health technologies. The result of an analysis by the Confidence Profile Method is a joint posterior probability distribution for the parameters of interest, from which marginal distributions for any particular parameter can be calculated. The method can be used to analyze problems involving a variety of types of outcomes, a variety of measures of effect, and a variety of experimental designs. This article presents the elements necessary for analysis, including prior distributions, likelihood functions, and specific models for experimental designs that include adjustment for biases.
本文介绍了一系列基于贝叶斯统计的荟萃分析技术，用于解释、调整和合并证据，以估计对卫生技术评估至关重要的参数和结果。置信剖面法的分析结果是感兴趣参数的联合后验概率分布，从中可以计算任何特定参数的边际分布。该方法可用于分析涉及多种类型结果、多种效应度量和多种实验设计的问题。本文介绍了分析所需的要素，包括先验分布、似然函数以及包含偏差调整的实验设计的具体模型。
