intercorrelation matrix mxMatrix(“Symm”, nrow=2, ncol=2, values=.8, free=T, name=“L”), # specify the matrix of unique factor variances mxMatrix(“Diag”, nrow=10, ncol=10, values=1, free=T, name=“U”), # specify the algebra that results in the model expectations mxAlgebra(A %*% L %*% t(A) + U, dimnames = list(indicators, indicators), name=“R” ), # specify a model for the means fixed at zero mxMatrix(“Full”, nrow=1, ncol=10, values=0, free=FALSE, dimnames=list(NULL, indicators), name=“M” ), # choose the full information maximum likelihood objective function mxFIMLObjective(covariance=“R”, means=“M”), # attach the data to the model mxData(factorData, type=“raw”) ) # run the factor model factorModelOut <- mxRun(factorModel) # print a summary of the results summary(factorModelOut)
