Description Usage Format Examples
This Covariance matrix was used as the population model for one set of simulations. It was used to represent a parallel data structure in which all factor loadings and error variances are set at .6 and the latent variables are correlated at .3.
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A covariance matrix of 20 theoretical items.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | ###---Loadings
fx<-t(matrix(c(
.6,0,0,0,0,
.6,0,0,0,0,
.6,0,0,0,0,
.6,0,0,0,0,
0,.6,0,0,0,
0,.6,0,0,0,
0,.6,0,0,0,
0,.6,0,0,0,
0,0,.6,0,0,
0,0,.6,0,0,
0,0,.6,0,0,
0,0,.6,0,0,
0,0,0,.6,0,
0,0,0,.6,0,
0,0,0,.6,0,
0,0,0,.6,0,
0,0,0,0,.6,
0,0,0,0,.6,
0,0,0,0,.6,
0,0,0,0,.6), nrow=5))
###--Error Variances
err<-diag(c(.6^2,.6^2,.6^2,.6^2,
.6^2,.6^2,.6^2,.6^2,
.6^2,.6^2,.6^2,.6^2,
.6^2,.6^2,.6^2,.6^2,
.6^2,.6^2,.6^2,.6^2))
###---5x5 matrix of factor covariances
phi<-matrix(c(rep(.3, 25)), nrow=5)
diag(phi)<-1
###---Reliability Calculation---###
t1<-matrix(c(rep(1,20)), nrow=1)
t1t<-matrix(c(rep(1,20)), ncol=1)
(fx%*%phi%*%t(fx)+err)
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