mlmWithCov: Uses covariance/correlation matrix to calculate multivariate...
In dominanceanalysis: Dominance Analysis

mlmWithCov

R Documentation

Uses covariance/correlation matrix to calculate multivariate index of fit

Description

Calculate R^2_{XY} and P^2_{YX} for multivariate regression Could be used with dominanceAnalysis to perform a multivariate dominance analysis without original data.

Usage

mlmWithCov(f, x)

Arguments

`f`	formula. Should use `cbind(y1,y2,...,yk)~x1+x2+..+xp`
`x`	correlation/covariance matrix

Value

`r.squared.xy`	`R^2_{XY}` of the regression
`p.squared.yx`	`P^2_{YX}` of the regression
`formula`	formula provided as parameter
`cov`	covariance/correlation matrix provided as parameter

Examples

library(car)
cor.m<-matrix(c(
 1.0000000, 0.7951377, 0.2617168, 0.6720053, 0.3390278,
 0.7951377, 1.0000000, 0.3341037, 0.5876337, 0.3404206,
 0.2617168, 0.3341037, 1.0000000, 0.3703162, 0.2114153,
 0.6720053, 0.5876337, 0.3703162, 1.0000000, 0.3548077,
 0.3390278, 0.3404206, 0.2114153, 0.3548077, 1.0000000),
 5,5,
 byrow = TRUE,
 dimnames = list(
   c("na","ss","SAT","PPVT","Raven"),
   c("na","ss","SAT","PPVT","Raven")))
lwith<-mlmWithCov(cbind(na,ss)~SAT+PPVT+Raven,cor.m)
da<-dominanceAnalysis(lwith)
print(da)
summary(da)

dominanceanalysis documentation built on May 29, 2024, 2:28 a.m.