rda: Redundancy Analysis

In mikewlcheung/mulsem: Some Multivariate Analyses using Structural Equation Modeling

Redundancy Analysis

Description

It conducts a redundancy analysis using the OpenMx package. Missing data are handled with the full information maximum likelihood method when raw data are available. It provides standard errors on the standardized estimates.

Usage

rda(X_vars, Y_vars, data=NULL, Cov, numObs, extraTries=50, ...)

Arguments

X_vars	A vector of characters of the X variables.
Y_vars	A vector of characters of the Y variables.
data	A data frame of raw data.
Cov	A covariance or correlation matrix if data is not available.
numObs	A sample size if data is not available.
extraTries	This function calls mxTryHard to obtain the parameter estimates and their standard errors. extraTries indicates the number of extra runs. If extraTries=0, mxRun is called.
...	Additional arguments sent to either mxTryHard or mxRun.

Value

A list of output with class RDA. It stores the model in OpenMx objects. The fitted object is in the slot of mx.fit.

Author(s)

Mike W.-L. Cheung <[e-mail]>

References

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. https://doi.org/10.1080/00273171.2022.2141675

See Also

Chittum19, sas_ex2

mikewlcheung/mulsem documentation built on Feb. 8, 2024, 11:03 a.m.