library("MASS") set.seed(42) D <-3 P <- 10 N <-1000 mu_theta <- rep(0,D) # the mean of eta mu_epsilon <- rep(0,P) # the mean of epsilon Phi <- diag(D) Psi <- diag(P) l1 <- c(0.99, 0.00, 0.25, 0.00, 0.80, 0.00, 0.50, 0.00, 0.00, 0.00) l2 <- c(0.00, 0.90, 0.25, 0.40, 0.00, 0.50, 0.00, 0.00, -0.30, -0.30) l3<- c(0.00, 0.00, 0.85, 0.80, 0.00, 0.75, 0.75, 0.00, 0.80, 0.80) L <-cbind(l1,l2,l3) # the loading matrix Theta <-mvrnorm(N, mu_theta, Phi) # sample factor scores Epsilon <-mvrnorm(N, mu_epsilon, Psi) # sample error vector Y<-Theta%*%t(L)+Epsilon# generate observable data
fa_model <- factanal(Y, D) fa_model$loadings <- fa_model$loadings[, c(2, 3, 1)] fa1 <- psych::fa(Y, nfactors = 3, rotate = "varimax") cbind(fa_model$loadings, L, fa1$loadings[,c(2, 3, 1)])
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.