{smcl} {* *! version 1.3.0 December 28, 2024 J. N. Luchman}{...} {cmd:help mvdom} {hline}{...} {title:Title} {pstd} Multivariate regression wrapper program for {cmd:domin}{p_end} {title:Syntax} {phang} {cmd:mvdom} {it:{help varname:depvar1}} {it:{help varlist:indepvars}} [{it:{help if}}] {weight}} {cmd:,} {opt dvs(depvar2 [... depvar_r])} [{opt pxy} {opt epsilon}] {phang}{cmd:aweight}s and {cmd:fweight}s are allowed (see help {help weights:weights}). {help fvvarlist: Factor} and {help tsvarlist:time series variables} are not allowed. {title:Description} {pstd} {cmd:mvdom} is a specialized {help mvreg:multivariate regression} command that is designed with a syntax structure that can be used in {help domin:dominance analysis}. {cmd:mvdom} also returns one of two model fit metrics recommended for use by Azen and Budescu (2006). These two fit metrics are the the {it:Rxy} and {it:Pxy} discussed by Van den Berg and Lewis (1988). For an example, see {cmd:domin}'s {help domin##examp:Example #6}. {pstd} {cmd:mvdom} uses the standard {it:depvar indepvars} syntax common to many estimation commands in Stata but extends on it by allowing additional {it:depvars} to be submitted in the {opt dvs()} option. {cmd:mvdom} requires at least two dependent variables, one submitted in the primary variable list (i.e., {it:depvar1}) and one or more submitted in the {opt dvs()} option (i.e., {it:depvar2 ... depvar_r}). Note that {cmd:domin} will only show the first dependent variable submitted in the output although all are used in model estimation. {pstd} {cmd:mixdom} is intended for use only as a wrapper program with {cmd:domin} and is not recommended for use as an estimation command outside of {cmd:domin}. As of version 1.3.0, {cmd:mvdom} is compatible with {cmd:domin}'s {help mi_dom} wrapper command. To do so, {cmd:mvdom} returns uninformative {cmd:b} and {cmd:V} matrices that are both values of 1. This is because {cmd:mvdom} is intended to be used only for its fit statistics and these two matrices are irrelevant for dominance analysis. {pstd} {cmd:mvdom} uses {help canon:canonical correlation} as its underlying estimation engine. {marker options}{...} {title:Options} {phang}{opt dvs(depvar2 [... depvar_r])} is a required option that specifies the second through {it:r}th dependent variables to be used in the multivariate regression. Note the first dependent variable, {it:depvar1}, is submitted in the overall variable list. {opt dvs()} must have at least one variable. {phang}{opt pxy} changes the fit statistic from the default "symmetric" {it:Rxy} to the "nonsymmetric" {it:Pxy} model fit statistic. {phang}{opt epsilon} changes the decomposition estimation method to relative weights estimation method described by LeBreton and Tonidandel (2008). The {opt epsilon} method produces a decomposition of the {it:Pxy} statistic. {title:Saved results} {phang}{cmd:mvdom} saves the following results to {cmd: e()}: {synoptset 16 tabbed}{...} {p2col 5 15 19 2: scalars}{p_end} {synopt:{cmd:e(r2)}}{it:Rxy} metric (default) or {it:Pxy} metric (with option {opt pxy}){p_end} {p2col 5 15 19 2: macros}{p_end} {synopt:{cmd:e(title)}}"Multivariate regression"{p_end} {synopt:{cmd:e(cmd)}}{cmd:mvdom}{p_end} {p2col 5 15 19 2: matrices}{p_end} {synopt:{cmd:e(b)}}1; required for {cmd:mi_dom}{p_end} {synopt:{cmd:e(V)}}1; required for {cmd:mi_dom}{p_end} {p2col 5 15 19 2: functions}{p_end} {synopt:{cmd:e(sample)}}marks estimation sample{p_end} {title:References} {p 4 8 2}Azen, R., & Budescu, D. V. (2006). Comparing predictors in multivariate regression models: An extension of dominance analysis. {it:Journal of Educational and Behavioral Statistics, 31(2)}, 157-180.{p_end} {p 4 8 2}LeBreton, J. M., & Tonidandel, S. (2008). Multivariate relative importance: Extending relative weight analysis to multivariate criterion spaces. {it:Journal of Applied Psychology, 93(2)}, 329-345.{p_end} {p 4 8 2}Van den Burg, W., & Lewis, C. (1988). Some properties of two measures of multivariate association. {it:Psychometrika, 53}, 109-122.{p_end} {title:Author} {p 4}Joseph N. Luchman{p_end} {p 4}Research Fellow{p_end} {p 4}Fors Marsh{p_end} {p 4}Arlington, VA{p_end} {p 4}jluchman@forsmarsh.com{p_end} {title:Also see} {psee} {manhelp mvreg R}, {manhelp canon R}. {p_end}