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Meta-Analysis with Binary Outcomes

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Meta-Analysis with R

Part of the book series: Use R! ((USE R))

Abstract

This chapter describes how to perform meta-analysis with binary data using R. We introduce the usual effect measures for binary outcomes and discuss issues raised by sparse binary data. We describe how to perform meta-analysis using the inverse variance method [17] and the DerSimonian–Laird method [12]. Furthermore, we introduce the Mantel–Haenszel method [24] and the Peto method [36] which are specific to binary outcomes. Several examples use base R commands. We also describe the metabin function from R package meta [31, 32] which provides a unified syntax for all methods in this chapter.

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Authors and Affiliations

  1. Institute for Medical Biometry and Statistics, Medical Center – University of Freiburg, Freiburg, Germany

    Guido Schwarzer & Gerta Rücker

  2. MRC Clinical Trials Unit, London and London School of Hygiene and Tropical Medicine, London, UK

    James R. Carpenter

Authors
  1. Guido Schwarzer
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  2. James R. Carpenter
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  3. Gerta Rücker
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Schwarzer, G., Carpenter, J.R., Rücker, G. (2015). Meta-Analysis with Binary Outcomes. In: Meta-Analysis with R. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-21416-0_3

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