Package: metasens 1.6-0

metasens: 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) <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>; - LFK index test and Doi plot by Furuya-Kanamori et al. (2018) <doi:10.1097/XEB.0000000000000141>.

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