diff --git a/R/BASS.R b/R/BASS.R
index 79f2641..c151d47 100644
--- a/R/BASS.R
+++ b/R/BASS.R
@@ -1,64 +1,52 @@
-BASS<-function(R, maxP=5, Print = "ON"){
-#---------------------------------------------------------
-
-# Program to compute Goldberg's Bass Ackwards Procedure
-# from a correlation matrix (R). PC with Varimax Rotation
-# Niels Waller, May 10, 2006
-#
-# Program arguments:
-# R = input correlation matrix
-# maxP = maximum number of components to rotate
-# Print = ON/OFF to print summarzed findings to screen
-#----------------------------------------------------------
-varNames <- rownames(R, do.NULL = FALSE, prefix = "var")
-
-ULU <- eigen(R)
-U <- ULU$vectors
-L <- ULU$values
-key <- sign(apply(U, 2, sum))
-key[key < 0] <- -1
-U <- U %*% diag(key)
-P <- U %*% diag(sqrt(L))
-p <- ncol(R)
-CrossLevelCors <- list(rep(0, p - 1))
-T <- list(rep(0, p - 1))
-PCloadings <- list(rep(0, p - 1))
-for (i in 2:maxP) {
-vout <- varimax(P[, 1:i], normalize = TRUE, eps = 1e-15)
-
-T[[i - 1]] <- vout$rotmat
-PCloadings[[i - 1]] <- vout$loadings[1:p, ]
-rownames(PCloadings[[i - 1]]) <- varNames
+BASS <- function(R, maxP = 5, Print = TRUE) {
+  # Program to compute Goldberg's Bass Ackwards Procedure
+  # from a correlation matrix (R). PC with Varimax Rotation
+  # Niels Waller, May 10, 2006
+  #
+  # Arguments:
+  # R: Input correlation matrix
+  # maxP: Maximum number of components to rotate
+  # Print: Boolean flag to print summarized findings to screen
+  
+  varNames <- rownames(R)
+  ULU <- eigen(R)
+  U <- ULU$vectors
+  L <- ULU$values
+  
+  key <- sign(apply(U, 2, sum))
+  key[key < 0] <- -1
+  U <- U %*% diag(key)
+  P <- U %*% diag(sqrt(L))
+  
+  p <- ncol(R)
+  CrossLevelCors <- vector("list", maxP - 1)
+  T <- vector("list", maxP - 1)
+  PCloadings <- vector("list", maxP - 1)
+  
+  for (i in 2:maxP) {
+    vout <- varimax(P[, 1:i], normalize = TRUE, eps = 1e-15)
+    T[[i - 1]] <- vout$rotmat
+    PCloadings[[i - 1]] <- vout$loadings[1:p, ]
+    rownames(PCloadings[[i - 1]]) <- varNames
+  }
+  
+  Z <- paste("Z", 1:maxP, sep = "")
+  V <- paste("V", 1:maxP, sep = "")
+  
+  if (Print) {
+    for (i in 1:(maxP - 1)) {
+      cat("\nCorrelation of", Z[i], "with", V[i + 1], "\n\n")
+      print(round(T[[i]][1, ], 3))
+    }
+  }
+  
+  for (i in 1:(maxP - 2)) {
+    S <- cbind(diag(i), matrix(0, i, 1))
+    out <- t(T[[i]]) %*% S %*% T[[i + 1]]
+    rownames(out) <- paste(V[i], ".", 1:i, sep = "")
+    colnames(out) <- paste(V[i + 1], ".", 1:(i + 1), sep = "")
+    CrossLevelCors[[i]] <- out
+  }
+  
+  list(T = T, cors = CrossLevelCors, loadings = PCloadings)
 }
-Z <- paste("Z", 1:maxP, sep = "")
-V <- paste("V", 1:maxP, sep = "")
-if (Print == "ON") {
-cat("nCorrelation of", Z[1], " with ", V[2], "n")
-
-}
-out <- T[[1]][1, ]
-dim(out) <- c(1, 2)
-rownames(out) <- Z[1]
-colnames(out) <- paste(V[2], ".", 1:2, sep = "")
-CrossLevelCors[[1]] <- out
-if (Print == "ON") {
-print(round(out, 3))
-
-}
-for (i in 2:(maxP - 1)) {
-if (Print == "ON") {
-cat("nnnCorrelation of", V[i], " with ", V[i + 1], "nn")
-
-}
-S <- cbind(diag(i), matrix(0, i, 1))
-out <- t(T[[i - 1]]) %*% S %*% T[[i]]
-rownames(out) <- paste(V[i], ".", 1:i, sep = "")
-colnames(out) <- paste(V[i + 1], ".", 1:(i + 1), sep = "")
-CrossLevelCors[[i]] <- out
-if (Print == "ON") {
-print(round(out, 3))
-
-}
-}
-invisible(list(T = T, cors = CrossLevelCors, loadings = PCloadings))
-}
\ No newline at end of file