Description Usage Format Examples

This covariance matrix was used as the population model for one set of simulations. It was used to represent a congeneric data structure in which the factor loadings are set at .5, .6, .7, .8, .5, .6, .7, and .8. The error variances were set at .6^2, .7^2, .8^2, .9^2, .6^2, .7^2, .8^2, and .9^2. The correlations between the latent variables was fixed to .3.

1 |

A covariance matrix of 12 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 | ```
###---Loadings
fx<-t(matrix(c(
.5,0,0,
.6,0,0,
.7,0,0,
.8,0,0,
0,.5,0,
0,.6,0,
0,.7,0,
0,.8,0,
0,0,.5,
0,0,.6,
0,0,.7,
0,0,.8), nrow=3))
###--Error Variances
err<-diag(c(.6^2,.7^2,.8^2,.9^2,
.6^2,.7^2,.8^2,.9^2,
.6^2,.7^2,.8^2,.9^2))
###---3x3 matrix of factor covariances
phi<-matrix(c(rep(.3, 9)), nrow=3)
diag(phi)<-1
###---Reliability Calculation---###
t1<-matrix(c(rep(1,12)), nrow=1)
t1t<-matrix(c(rep(1,12)), ncol=1)
(fx%*%phi%*%t(fx)+err)
``` |

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