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The mulSEM package includes 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).

You may install it from CRAN by:

install.packages("mulSEM")

The developmental version can be installed from GitHub by:

## Install remotes package if it has not been installed yet
# install.packages("remotes")

remotes::install_github("mikewlcheung/mulsem")

library(mulSEM)

## Canonical Correlation Analysis
cancorr(X_vars=c("Weight", "Waist", "Pulse"),
        Y_vars=c("Chins", "Situps", "Jumps"),
        data=sas_ex1)

## Redundancy Analysis
rda(X_vars=c("x1", "x2", "x3", "x4"),
    Y_vars=c("y1", "y2", "y3"),
    data=sas_ex2)
	
## Multivariate Principal Component Regression	
mpcr(X_vars=c("AU", "CC", "CL", "CO", "DF", "FB", "GR", "MW"),
     Y_vars=c("IDE", "IEE", "IOCB", "IPR", "ITS"),
     pca="COR", pc_select=1,
     data=Nimon21)

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Install

install.packages('mulSEM')

Monthly Downloads

171

Version

1.0

License

GPL (>= 2)

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Maintainer

Mike Cheung

Last Published

February 4th, 2024

Functions in mulSEM (1.0)

Chittum19

Correlation matrix of a model of motivation
rda

Redundancy Analysis
sas_ex1

Sample data for canonical correlation analysis from the SAS manual
Lambert88

Correlation matrix of artificial data
Thorndike00

Correlation matrix of a model of disgust
Nimon21

Raw data used in Nimon, Joo, and Bontrager (2021)
mpcr

Multivariate Principal Component Regression (MPCR)
cancorr

Canonical Correlation Analysis
print

Print Methods for various Objects
mulSEM-package

Some Multivariate Analyses using Structural Equation Modeling
sas_ex2

Sample data for redundancy analysis from the SAS manual