metasens: Advanced Statistical Methods to Model and Adjust for Bias in Meta-Analysis

The following methods are implemented to evaluate how sensitive the results of a meta-analysis are to potential bias in meta-analysis and to support Schwarzer et al. (2015) <DOI:10.1007/978-3-319-21416-0>, Chapter 5 'Small-Study Effects in Meta-Analysis': - Copas selection model described in Copas & Shi (2001) <DOI:10.1177/096228020101000402>; - limit meta-analysis by Rücker et al. (2011) <DOI:10.1093/biostatistics/kxq046>; - upper bound for outcome reporting bias by Copas & Jackson (2004) <DOI:10.1111/j.0006-341X.2004.00161.x>; - imputation methods for missing binary data by Gamble & Hollis (2005) <DOI:10.1016/j.jclinepi.2004.09.013> and Higgins et al. (2008) <DOI:10.1177/1740774508091600>.

Package details

AuthorGuido Schwarzer [cre, aut] (<>), James R. Carpenter [aut] (<>), Gerta Rücker [aut] (<>)
MaintainerGuido Schwarzer <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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metasens documentation built on July 8, 2020, 7:16 p.m.