bmem: Mediation Analysis with Missing Data Using Bootstrap

Four methods for mediation analysis with missing data: Listwise deletion, Pairwise deletion, Multiple imputation, and Two Stage Maximum Likelihood algorithm. For MI and TS-ML, auxiliary variables can be included. Bootstrap confidence intervals for mediation effects are obtained. The robust method is also implemented for TS-ML. Since version 1.4, bmem adds the capability to conduct power analysis for mediation models. Details about the methods used can be found in these articles. Zhang and Wang (2003) <doi:10.1007/s11336-012-9301-5>. Zhang (2014) <doi:10.3758/s13428-013-0424-0>.

Version:	1.8
Depends:	R (≥ 1.7), Amelia, MASS, snowfall
Imports:	lavaan, sem
Published:	2020-09-19
Author:	Zhiyong Zhang and Lijuan Wang
Maintainer:	Zhiyong Zhang <zhiyongzhang at nd.edu>
License:	GPL-2
URL:	https://bigdatalab.nd.edu
NeedsCompilation:	no
CRAN checks:	bmem results

Documentation:

Reference manual:

bmem.pdf

Downloads:

Package source:	bmem_1.8.tar.gz
Windows binaries:	r-devel: bmem_1.8.zip, r-release: bmem_1.8.zip, r-oldrel: bmem_1.8.zip
macOS binaries:	r-release (arm64): bmem_1.8.tgz, r-oldrel (arm64): bmem_1.8.tgz, r-release (x86_64): bmem_1.8.tgz, r-oldrel (x86_64): bmem_1.8.tgz
Old sources:	bmem archive

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