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)
A matrix of loadings.
A matrix of factor correlations
Should the diagonal be model by ff' (U2 = TRUE) or replaced with 1's (U2 = FALSE)
A correlation or covariance matrix.
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/)
# NOT RUN {
f2 <- matrix(c(.9,.8,.7,rep(0,6),.6,.7,.8),ncol=2)
mod <- factor.model(f2)
round(mod,2)
# }
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