*! version 1.2.0 August 14, 2023 J. N. Luchman
help mvdom

Title

Wrapper program for domin to conduct multivariate regression-based dominance analysis

Syntax

mvdom depvar1 indepvars if [weight] ,
dvs(depvar2 [... depvar_r]) [pxy epsilon]

aweights and fweights are allowed (see help weights). Factor and time series variables are not allowed. Use the xi prefix for factor variables.

Description

mvdom sets the data up in a way to allow for the dominance analysis of a multivariate regression by utilizing canonical correlation. The default metric used is the Rxy metric described by Azen and Budescu (2006).

mvdom uses the first variable in the varlist as the first dependent variable in the multivariate regression. All other variables in the varlist are used as independent variables. All dependent variables after the first are entered into the regression in the dvs() option. domin will only show the first dependent variable in the output.

mvdom is intended for use only as a wrapper program with domin for the dominance analysis of multivariate linear regression, and its syntax is designed to conform with domin's expectations.
It is not recommended for use as an estimation command outside of domin.

Options

dvs(depvar2 [... depvar_r]) specifies the second through rth other dependent variables to be used in the multivariate regression. Note the first dependent variable, depvar1, as shown in the syntax. dvs() is required.

pxy changes the fit statistic from the default "symmetric" Rxy to the "nonsymmetric" Pxy model fit statistic. Both fit statistics are described by Azen and Budescu (2006).

epsilon changes the decomposition estimation method to relative weights estimation method described by LeBreton & Tonidandel (2008). The epsilon method produces a decomposition of the Pxy statistic.

Saved results

mvdom saves the following results to e():

scalars

e(r2) Rxy metric (default) or Pxy metric (with option pxy)

macros

e(title) "Multivariate regression"

functions

e(sample) marks estimation sample

References

Azen, R., & Budescu, D. V. (2006). Comparing predictors in multivariate regression models: An extension of dominance analysis. Journal of Educational and Behavioral Statistics, 31(2), 157-180.

LeBreton, J. M., & Tonidandel, S. (2008). Multivariate relative importance: Extending relative weight analysis to multivariate criterion spaces. Journal of Applied Psychology, 93(2), 329-345.

Author

Joseph N. Luchman

Research Fellow

Fors Marsh

Arlington, VA

jluchman@forsmarsh.com

Also see

[R] mvreg,
[R] canon.