Performing Arm-Based Network Meta-Analysis in R with the pcnetmeta Package
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| Authors | Lifeng Lin, Jing Zhang, James S. Hodges, Haitao Chu |
| Journal/Conference Name | Journal of statistical software |
| Paper Category | Other |
| Paper Abstract | 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. |
| Date of publication | 2017 |
| Code Programming Language | R |
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