Nothing
"print_psych.iclust" <-
function(x,digits=2,all=FALSE,cut=NULL,sort=FALSE,...) {
cat("ICLUST (Item Cluster Analysis)")
cat("\nCall: ")
print(x$call)
if((!is.null(x$purify)) && x$purify) {
cat("\nPurified Alpha:\n")
print(x$purified$alpha,digits)
cat("\nG6* reliability:\n")
print(x$purified$G6,digits)
cat("\nOriginal Beta:\n")
print(x$beta,digits)
cat("\nCluster size:\n")
print(x$purified$size,digits)
} else
{
cat("\noriginal Alpha:\n")
print(x$alpha,digits)
cat("\nG6* reliability:\n")
print(x$G6,digits)
cat("\nOriginal Beta:\n")
print(x$beta,digits)
cat("\nCluster size:\n")
print(x$size,digits)}
if(sort) { cat("\nItem by Cluster Structure matrix: Sorted by loading \n")
load <- x$sorted$sorted
if(is.null(cut)) cut <- .3
ncol <- dim(load)[2]-3
load[4:(ncol+3)] <- round(load[4:(ncol+3)],digits)
fx <- as.matrix(format(load,digits=digits))
nc <- nchar(fx[1,4], type = "c")
fx.1 <- fx[,1:3]
fx.2 <- format(fx[,4:(3+ncol)],digits)
load.2 <- load[,4:(ncol+3)]
fx.2[abs(load.2)< cut] <- paste(rep(" ", nc), collapse = "")
fx <- data.frame(fx.1,fx.2)
print(fx,quote="FALSE")
eigenvalues <- diag(t(x$pattern) %*% x$loadings)
cat("\nWith Sums of squares of:\n")
print(eigenvalues,digits=digits)
}
else {if(is.null(cut)) cut <- 0 #added 8/9/16
cat("\nItem by Cluster Structure matrix:\n")
load <- unclass(x$loadings)
load <- round(load,digits)
fx <- format(load,digits=digits)
nc <- nchar(fx[1,1], type = "c")
fx[abs(load) < cut] <- paste(rep(" ", nc), collapse = "")
if(is.matrix(x$clusters)) {
clust <- colnames(x$clusters)[apply(abs(x$clusters),1,which.max)]
pclust <- colnames(x$p.sorted$clusters)[apply(abs(x$p.sorted$clusters),1,which.max)]
clust.fx <- data.frame(O=clust,P=pclust,fx)} else {clust.fx <- fx}
print(clust.fx,quote="FALSE")
#print(unclass(x$loadings))
eigenvalues <- diag(t(x$pattern) %*% x$loadings)
cat("\nWith Sums of squares of:\n")
print(eigenvalues,digits=digits)
}
if(!is.null(x$purified$cor)) {cat("\nPurified scale intercorrelations\n reliabilities on diagonal\n correlations corrected for attenuation above diagonal: \n")
print(round(x$purified$corrected,digits=digits)) }
cat("\nCluster fit = ",round(x$fit$clusterfit,digits), " Pattern fit = ",round(x$fit$patternfit,digits), " RMSR = ",round(x$fit$patternrmse,digits), "\n")
}# end of print.psych.ICLUST
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