Package: bmemLavaan 0.5

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>).

Authors:Shuigen Ming [aut], Hong Zhang [aut], Zhiyong Zhang [aut, cre], Lijuan Wang [aut]

bmemLavaan_0.5.tar.gz
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bmemLavaan_0.5.tgz(r-4.4-any)bmemLavaan_0.5.tgz(r-4.3-any)
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bmemLavaan.pdf |bmemLavaan.html
bmemLavaan/json (API)

# Install 'bmemLavaan' in R:
install.packages('bmemLavaan', repos = c('https://johnnyzhz.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • Math - Parents' education levels and adolescent mathematics achievement of 76 families in 1986

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 266 downloads 5 exports 27 dependencies

Last updated 2 years agofrom:6cd9892923. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 14 2024
R-4.5-winNOTENov 14 2024
R-4.5-linuxNOTENov 14 2024
R-4.4-winOKNov 14 2024
R-4.4-macOKNov 14 2024
R-4.3-winOKNov 14 2024
R-4.3-macOKNov 14 2024

Exports:bmempower.bmempower.curvesummary.bmemsummary.power

Dependencies:abindAmeliaarmbootcodaforeignlatticelavaanlme4MASSMatrixmiminqamnormtnlmenloptrnumDerivpbivnormquadprogRcppRcppArmadilloRcppEigenrlangrsemsemsnowsnowfall

R package: bmemLavaan vignette

Rendered fromR_package-bmemLavaan_vignette.pdf.asisusingR.rsp::asison Nov 14 2024.

Last update: 2022-04-20
Started: 2022-04-20