mulSEM-package {mulSEM} | R Documentation |
Some Multivariate Analyses using Structural Equation Modeling
Description
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>.
Author(s)
Mike W.-L. Cheung <mikewlcheung@nus.edu.sg>, Fei Gu <gu@vt.edu>, Yiu-Fai Yung <Yiu-Fai.Yung@sas.com>
Maintainer: Mike W.-L. Cheung <mikewlcheung@nus.edu.sg>
References
Gu, F., & Cheung, M. W.-L. (2023). A Model-based approach to multivariate principal component regression: Selection of principal components and standard error estimates for unstandardized regression coefficients. British Journal of Mathematical and Statistical Psychology, 76(3), 605-622. https://doi.org/10.1111/bmsp.12301
Gu, F., Yung, Y.-F., & Cheung, M. W.-L. (2019). Four covariance structure models for canonical correlation analysis: A COSAN modeling approach. Multivariate Behavioral Research, 54(2), 192-223. https://doi.org/10.1080/00273171.2018.1512847
Gu, F., Yung, Y.-F., Cheung, M. W.-L. Joo, B.-K., & Nimon, K. (2022). Statistical inference in redundancy analysis: A direct covariance structure modeling approach. Multivariate Behavioral Research, 58(5), 877-893. https://doi.org/10.1080/00273171.2022.2141675
Examples
## 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)