bmemLavaan: Mediation Analysis with Missing Data and Non-Normal Data

Methods for mediation analysis with missing data and non-normal data are implemented. For missing data, four methods are available: Listwise deletion, Pairwise deletion, Multiple imputation, and Two Stage Maximum Likelihood algorithm. For MI and TS-ML, auxiliary variables can be included to handle missing data. For handling non-normal data, bootstrap and two-stage robust methods can be used. Technical details of the methods can be found in Zhang and Wang (2013, <doi:10.1007/s11336-012-9301-5>), Zhang (2014, <doi:10.3758/s13428-013-0424-0>), and Yuan and Zhang (2012, <doi:10.1007/s11336-012-9282-4>).

Version: 0.5
Depends: R (≥ 3.5.0), Amelia, MASS, snowfall, rsem
Imports: lavaan, sem
Suggests: R.rsp
Published: 2022-05-28
DOI: 10.32614/CRAN.package.bmemLavaan
Author: Shuigen Ming [aut], Hong Zhang [aut], Zhiyong Zhang [aut, cre], Lijuan Wang [aut]
Maintainer: Zhiyong Zhang <johnnyzhz at>
License: GPL-2
NeedsCompilation: no
In views: MissingData
CRAN checks: bmemLavaan results


Reference manual: bmemLavaan.pdf
Vignettes: R package: bmemLavaan vignette


Package source: bmemLavaan_0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): bmemLavaan_0.5.tgz, r-oldrel (arm64): bmemLavaan_0.5.tgz, r-release (x86_64): bmemLavaan_0.5.tgz, r-oldrel (x86_64): bmemLavaan_0.5.tgz
Old sources: bmemLavaan archive

Reverse dependencies:

Reverse suggests: semmcci


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