Statistical Methods for Sensitivity Analysis 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) , Chapter 5 'Small-Study Effects in Meta-Analysis': - Copas selection model described in Copas & Shi (2001) ; - limit meta-analysis by Rücker et al. (2011) ; - upper bound for outcome reporting bias by Copas & Jackson (2004) ; - imputation methods for missing binary data by Gamble & Hollis (2005) and Higgins et al. (2008) ; - LFK index test and Doi plot by Furuya-Kanamori et al. (2018) .


Reference manual

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install.packages("metasens")

1.5-3 by Guido Schwarzer, a year ago


https://github.com/guido-s/metasens, https://link.springer.com/book/10.1007/978-3-319-21416-0


Browse source code at https://github.com/cran/metasens


Authors: Guido Schwarzer [cre, aut] (ORCID: , James R. Carpenter [aut] (ORCID: , Gerta Rücker [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Depends on meta


Suggested by metabook, metadat.


See at CRAN