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mulSEM: Some Multivariate Analyses using Structural Equation Modeling

A set of functions for some multivariate analyses utilizing a structural equation modeling (SEM) approach through the 'OpenMx' package. These analyses include canonical correlation analysis (CANCORR), redundancy analysis (RDA), and multivariate principal component regression (MPCR). It implements procedures discussed in Gu and Cheung (2023) <doi:10.1111/bmsp.12301>, Gu, Yung, and Cheung (2019) <doi:10.1080/00273171.2018.1512847>, and Gu et al. (2023) <doi:10.1080/00273171.2022.2141675>.

Version: 1.0
Depends: R (≥ 3.5.0), OpenMx
Imports: stats
Published: 2024-02-04
Author: Mike Cheung ORCID iD [aut, cre], Fei Gu ORCID iD [ctb], Yiu-Fai Yung [ctb]
Maintainer: Mike Cheung <mikewlcheung at nus.edu.sg>
BugReports: https://github.com/mikewlcheung/mulsem/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/mikewlcheung/mulsem
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mulSEM results

Documentation:

Reference manual: mulSEM.pdf

Downloads:

Package source: mulSEM_1.0.tar.gz
Windows binaries: r-devel: mulSEM_1.0.zip, r-release: mulSEM_1.0.zip, r-oldrel: mulSEM_1.0.zip
macOS binaries: r-release (arm64): mulSEM_1.0.tgz, r-oldrel (arm64): mulSEM_1.0.tgz, r-release (x86_64): mulSEM_1.0.tgz, r-oldrel (x86_64): mulSEM_1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.