Description Usage Arguments Value Examples
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.
1 | mlmWithCov(f, x)
|
f |
formula. Should use |
x |
correlation/covariance matrix |
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 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | 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)
|
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