mulSEM (version 1.2)

mulSEM-package: mulSEM: 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) tools:::Rd_expr_doi("10.1111/bmsp.12301"), Gu, Yung, and Cheung (2019) tools:::Rd_expr_doi("10.1080/00273171.2018.1512847"), and Gu et al. (2023) tools:::Rd_expr_doi("10.1080/00273171.2022.2141675").

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

Maintainer: Mike Cheung (ORCID)

Other contributors:

• Fei Gu (ORCID) [contributor]

• Yiu-Fai Yung [contributor]

Mike W.-L. Cheung , Fei Gu , Yiu-Fai Yung

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. tools:::Rd_expr_doi("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. tools:::Rd_expr_doi("10.1080/00273171.2018.1512847")

Gu, F., Yung, Y.-F., Cheung, M. W.-L., Joo, B.-K., & Nimon, K. (2023). Statistical inference in redundancy analysis: A direct covariance structure modeling approach. Multivariate Behavioral Research, 58(5), 877-893. tools:::Rd_expr_doi("10.1080/00273171.2022.2141675")

See Also

Useful links:

• https://github.com/mikewlcheung/mulsem

• Report bugs at https://github.com/mikewlcheung/mulsem/issues

Examples

# \donttest{
## 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)
# }