less CIs

R/CIM.R

@@ -420,46 +420,60 @@ CIM <- function(data,
             }
 
             ### Make dataframe with factor loading confidence intervals
-            if ('psych' %in% class(efa)) {
+            if (n.itr > 1)
+              if ('psych' %in% class(efa)) {
 
-              factorLoadingCIs[[rowVar]][[colVar]] <-
-                ufs::faConfInt(res$intermediate$efas[[rowVar]][[colVar]]);
-              loadingCIs <-
-                factorLoadingCIs[[rowVar]][[colVar]];
+                factorLoadingCIs[[rowVar]][[colVar]] <-
+                  ufs::faConfInt(res$intermediate$efas[[rowVar]][[colVar]]);
+                loadingCIs <-
+                  factorLoadingCIs[[rowVar]][[colVar]];
 
-              ciSummaryList[[rowIndex]][[colIndex]] <-
-                (loadingCIs[[1]]$hi < loadingCIs[[2]]$lo) |
-                (loadingCIs[[2]]$hi < loadingCIs[[1]]$lo);
+                ciSummaryList[[rowIndex]][[colIndex]] <-
+                  (loadingCIs[[1]]$hi < loadingCIs[[2]]$lo) |
+                  (loadingCIs[[2]]$hi < loadingCIs[[1]]$lo);
 
-              faDf <- matrix(unlist(factorLoadingCIs[[rowVar]][[colVar]]),
-                             ncol=6);
-            } else {
-              faDf <- matrix(rep(NA, 6*ncol(abbrVarsDat)),
-                             ncol=6);
-            }
+                faDf <- matrix(unlist(factorLoadingCIs[[rowVar]][[colVar]]),
+                               ncol=6);
 
-            ### Get abbreviated scale names
-            abbr <- abbreviate(names(scales));
+              } else {
+                faDf <- matrix(rep(NA, 6*ncol(abbrVarsDat)),
+                               ncol=6);
 
-            ### Set row and column names
-            rownames(faDf) <- c(abbrScales[[abbrScaleNames[rowVar]]],
-                                abbrScales[[abbrScaleNames[colVar]]]);
-                                # paste0(abbr[rowVar], 1:length(scales[[rowVar]])),
-                                # paste0(abbr[colVar], 1:length(scales[[colVar]])));
-            colnames(faDf) <- c(rep(c('lo', 'est', 'hi'), 2));
+              }
+              colnames(faDf) <- c(rep(c('lo', 'est', 'hi'), 2));
 
-            faDfReordered <- faDf[order(rownames(faDf)),
-                                  ];
-            res$intermediate$faDfs[[rowVar]][[colVar]] <-
-              list(faDf_raw = faDf,
-                   faDf = faDfReordered,
-                   faDf_rounded = round(faDfReordered, 2));
+          } else {
 
-            if (ufs::opts$get('debug')) {
-              cat0("\n\nJust stored this dataframe to create a gTable later on:\n\n");
-              print(res$intermediate$faDfs[[rowVar]][[colVar]]$faDf_rounded);
-              cat0("\n\n");
-            }
+            faDf <-
+              data.frame(
+                unclas(
+                  res$intermediate$efas[[rowVar]][[colVar]]
+                )
+              );
+
+          }
+
+          ### Get abbreviated scale names
+          abbr <- abbreviate(names(scales));
+
+          ### Set row and column names
+          rownames(faDf) <- c(abbrScales[[abbrScaleNames[rowVar]]],
+                              abbrScales[[abbrScaleNames[colVar]]]);
+          # paste0(abbr[rowVar], 1:length(scales[[rowVar]])),
+          # paste0(abbr[colVar], 1:length(scales[[colVar]])));
+
+          faDfReordered <- faDf[order(rownames(faDf)),
+          ];
+          res$intermediate$faDfs[[rowVar]][[colVar]] <-
+            list(faDf_raw = faDf,
+                 faDf = faDfReordered,
+                 faDf_rounded = round(faDfReordered, 2));
+
+          if (ufs::opts$get('debug')) {
+            cat0("\n\nJust stored this dataframe to create a gTable later on:\n\n");
+            print(res$intermediate$faDfs[[rowVar]][[colVar]]$faDf_rounded);
+            cat0("\n\n");
+          }
 
             ###------------------------------------------------------------------
             ###------------------------------------------------------------------