Journal of Statistical Software (Mar 2023)

netmeta: An R Package for Network Meta-Analysis Using Frequentist Methods

  • Sara Balduzzi,
  • Gerta Rücker,
  • Adriani Nikolakopoulou,
  • Theodoros Papakonstantinou,
  • Georgia Salanti,
  • Orestis Efthimiou,
  • Guido Schwarzer

DOI
https://doi.org/10.18637/jss.v106.i02
Journal volume & issue
Vol. 106
pp. 1 – 40

Abstract

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Network meta-analysis compares different interventions for the same condition, by combining direct and indirect evidence derived from all eligible studies. Network metaanalysis has been increasingly used by applied scientists and it is a major research topic for methodologists. This article describes the R package netmeta, which adopts frequentist methods to fit network meta-analysis models. We provide a roadmap to perform network meta-analysis, along with an overview of the main functions of the package. We present three worked examples considering different types of outcomes and different data formats to facilitate researchers aiming to conduct network meta-analysis with netmeta.

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