对比度(视觉)
荟萃分析
计算机科学
成对比较
灵活性(工程)
网络分析
网络模型
人工智能
机器学习
统计
数学
工程类
医学
电气工程
内科学
作者
Amalia Karahalios,Joanne E. McKenzie,Ian R. White
出处
期刊:Methods in molecular biology
日期:2021-09-22
卷期号:: 203-221
被引量:6
标识
DOI:10.1007/978-1-0716-1566-9_13
摘要
Network meta-analysis is used to synthesize evidence from a network of treatments. The models used in a network meta-analysis are more complex than those used for pairwise meta-analysis. Two types of models are available to undertake a network meta-analysis: contrast-based and arm-based models. Contrast-based models have been used in most published network meta-analyses. Arm-based models offer greater flexibility and handle treatments symmetrically, but risk compromising randomization. In this chapter, we (1) present the contrast-based and arm-based statistical models; (2) describe the theoretical differences between the models (noting when the estimates from the models are expected to diverge); (3) summarize the evidence comparing the two models from simulation studies and empirical investigations; and (4) provide a worked example applying the two models to a network using the R software package.
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