Performing Arm-Based Network Meta-Analysis in R with the pcnetmeta Package

被引:94
|
作者
Lin, Lifeng [1 ]
Zhang, Jing [2 ]
Hodges, James S. [1 ]
Chu, Haitao [1 ]
机构
[1] Univ Minnesota, Sch Publ Hlth, Div Biostat, Minneapolis, MN 55455 USA
[2] Univ Maryland, Sch Publ Hlth, Dept Epidemiol & Biostat, College Pk, MD 20740 USA
来源
JOURNAL OF STATISTICAL SOFTWARE | 2017年 / 80卷 / 05期
关键词
absolute effect; arm-based method; Bayesian inference; network meta-analysis; CHAIN MONTE-CARLO; CLINICAL-TRIALS; OUTCOMES; INCONSISTENCY; FRAMEWORK; ABSOLUTE; MODELS; EVENT;
D O I
10.18637/jss.v080.i05
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Network meta-analysis is a powerful approach for synthesizing direct and indirect evidence about multiple treatment comparisons from a collection of independent studies. At present, the most widely used method in network meta-analysis is contrast-based, in which a baseline treatment needs to be specified in each study, and the analysis focuses on modeling relative treatment effects (typically log odds ratios). However, population-averaged treatment-specific parameters, such as absolute risks, cannot be estimated by this method without an external data source or a separate model for a reference treatment. Recently, an arm-based network meta-analysis method has been proposed, and the R package pcnetmeta provides user-friendly functions for its implementation. This package estimates both absolute and relative effects, and can handle binary, continuous, and count outcomes.
引用
收藏
页码:1 / 25
页数:25
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