factor.model {psych} | R Documentation |
The basic factor or principal components model is that a correlation or covariance matrix may be reproduced by the product of a factor loading matrix times its transpose. Find this reproduced matrix. Used by factor.fit
, VSS
, ICLUST
, etc.
factor.model(f,Phi=NULL,U2=TRUE)
f |
A matrix of loadings. |
Phi |
A matrix of factor correlations |
U2 |
Should the diagonal be model by ff' (U2 = TRUE) or replaced with 1's (U2 = FALSE) |
A correlation or covariance matrix.
revelle@northwestern.edu
https://personality-project.org/revelle.html
Gorsuch, Richard, (1983) Factor Analysis. Lawrence Erlebaum Associates.
Revelle, W. In preparation) An Introduction to Psychometric Theory with applications in R (https://personality-project.org/r/book/)
ICLUST.graph
,ICLUST.cluster
, cluster.fit
, VSS
, omega
f2 <- matrix(c(.9,.8,.7,rep(0,6),.6,.7,.8),ncol=2)
mod <- factor.model(f2)
round(mod,2)