成对比较
计算机科学
贝叶斯网络
荟萃分析
工作流程
贝叶斯概率
排名(信息检索)
变阶贝叶斯网络
贝叶斯统计
编码(集合论)
数据挖掘
机器学习
人工智能
贝叶斯推理
医学
数据库
内科学
集合(抽象数据类型)
程序设计语言
作者
Dapeng Hu,Annette M. O’Connor,Chong Wang,Jan M. Sargeant,Charlotte B. Winder
标识
DOI:10.3389/fvets.2020.00271
摘要
Network meta-analysis is a general approach to integrate the results of multiple studies in which multiple treatments are compared, often in a pairwise manner. In this tutorial, we illustrate the procedures for conducting a network meta-analysis for binary outcomes data in the Bayesian framework using example data. Our goal is to describe the workflow of such an analysis and to explain how to generate informative results such as ranking plots and treatment risk posterior distribution plots. The R code used to conduct a network meta-analysis in the Bayesian setting is provided at GitHub.
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