fixed issue with options for CFA

inst/shiny/server.R

@@ -4,32 +4,32 @@ library(psych)
 library(lavaan)
 library(semPlot)
 shinyServer(function(input, output) {
-    
+
    bscfa <- reactive({
      x <- read.csv(text=input$textcfa, sep="\t")
      describe(x)[2:13]
-   })  
+   })
 
     bsgcm <- reactive({
         x <- read.csv(text=input$textgcm, sep="\t")
         describe(x)[2:13]
     })
-    
+
     bssem <- reactive({
       x <- read.csv(text=input$textsem, sep="\t")
       describe(x)[2:13]
-    })  
-    
+    })
+
     correl.cfa <- reactive({
       x <- read.csv(text=input$textcfa, sep="\t")
       round(cor(cbind(x), use = "complete"),3)
-    })    
-    
+    })
+
     correl.gcm <- reactive({
         x <- read.csv(text=input$textgcm, sep="\t")
         round(cor(cbind(x), use = "complete"),3)
     })
-    
+
     correl.sem <- reactive({
       x <- read.csv(text=input$textsem, sep="\t")
       round(cor(cbind(x), use = "complete"),3)
@@ -39,7 +39,7 @@ shinyServer(function(input, output) {
       x <- read.csv(text=input$textcfa, sep="\t")
       pairs.panels(x)
     }
-    
+
     makecorPlot.gcm <- function(){
         x <- read.csv(text=input$textgcm, sep="\t")
         pairs.panels(x)
@@ -52,77 +52,77 @@ shinyServer(function(input, output) {
     output$corPlot.cfa <- renderPlot({
       print(makecorPlot.cfa())
     })
-    
+
     output$corPlot.gcm <- renderPlot({
       print(makecorPlot.gcm())
     })
-    
+
     output$corPlot.sem <- renderPlot({
         print(makecorPlot.sem())
     })
-    
+
     get.textcfa <- reactive({
       input$cfamodel
     })
-    
+
     get.textgcm <- reactive({
         input$gcmmodel
     })
-    
+
     get.textsem <- reactive({
       input$semmodel
     })
-    
+
     est.cfa <- reactive({
       dat <- read.csv(text=input$textcfa, sep="\t")
-      
+
       model <- get.textcfa()
-      
-      fit <- cfa(model, data=dat)
-      
+
+      fit <- cfa(model, data=dat, estimator = input$estimatoroptions, se = input$seoptions, bootstrap = input$bootstrapoptions)
+
       list(fit = fit)
     })
-    
+
     est.gcm <- reactive({
         dat <- read.csv(text=input$textgcm, sep="\t")
-        
+
          model <- get.textgcm()
-         
+
          fit <- growth(model, data=dat, estimator = input$estimatoroptions, se = input$seoptions, bootstrap = input$bootstrapoptions)
 
         list(fit = fit)
     })
-    
+
     est.sem <- reactive({
       dat <- read.csv(text=input$textsem, sep="\t")
-      
+
       model <- get.textsem()
-      
+
       fit <- sem(model, data=dat, estimator = input$estimatoroptions, se = input$seoptions, bootstrap = input$bootstrapoptions)
-      
+
       list(fit = fit)
     })
-    
+
     result.cfa <- reactive({
-      
+
       rescfa <- est.cfa()$fit
       summary(rescfa, standardized=TRUE, fit.measures=TRUE)
-      
-    })    
+
+    })
     result.gcm <- reactive({
 
         resgcm <- est.gcm()$fit
         summary(resgcm, standardized=TRUE, fit.measures=TRUE)
-        
+
     })
-    
+
     result.sem <- reactive({
-      
+
       ressem <- est.sem()$fit
       summary(ressem, standardized=TRUE, fit.measures=TRUE)
-      
+
     })
-    
+
     makecfaplot1 <- function(){
       rescfa <- est.cfa()$fit
       semPaths(rescfa, "par", mar=c(3,4,3,4), style="ram", layout ="tree", edge.label.cex=.8, fade=F, gray=T)
@@ -131,53 +131,53 @@ shinyServer(function(input, output) {
       resgcm <- est.gcm()$fit
       semPaths(resgcm, "par", mar=c(3,4,3,4), style="ram", layout ="tree", edge.label.cex=.8, fade=F, gray=T)
     }
-    
+
     makesemplot1 <- function(){
       ressem <- est.sem()$fit
       semPaths(ressem, "par", mar=c(3,4,3,4), style="ram", layout ="tree", edge.label.cex=.8, fade=F, gray=T)
-    }    
+    }
 
     output$cfaplot1 <- renderPlot({
       print(makecfaplot1())
     })
-    
+
     output$gcmplot1 <- renderPlot({
       print(makegcmplot1())
     })
-    
+
     output$semplot1 <- renderPlot({
       print(makesemplot1())
     })
-    
+
     makegcmplot2 <- function(){
       resgcm <- est.gcm()$fit
       semPaths(resgcm, "par", mar=c(3,4,3,4), style="ram", layout ="tree", edge.label.cex=.8, fade=F, gray=T)
     }
     makecfaplot2 <- function(){
       rescfa <- est.cfa()$fit
       semPaths(rescfa, "par", mar=c(3,4,3,4), style="ram", layout ="tree", edge.label.cex=.8, fade=F, gray=T)
-    }   
-    
+    }
+
     makesemplot2 <- function(){
       ressem <- est.sem()$fit
       semPaths(ressem, "par", mar=c(3,4,3,4), style="ram", layout ="tree", edge.label.cex=.8, fade=F, gray=T)
-    } 
-    
+    }
+
     output$cfaplot2 <- renderPlot({
       print(makecfaplot1())
-    })   
-    
+    })
+
     output$gcmplot2 <- renderPlot({
       print(makegcmplot1())
     })
-    
+
     output$semplot2 <- renderPlot({
       print(makesemplot1())
     })
    ################################################
    # R session info
    ################################################
-   
+
    info <- reactive({
      info1 <- paste("This analysis was conducted with ", strsplit(R.version$version.string, " \\(")[[1]][1], ".", sep = "")
      info2 <- paste("It was executed on ", date(), ".", sep = "")
@@ -197,7 +197,7 @@ shinyServer(function(input, output) {
      cat(sprintf(info5), "\n")
      cat(sprintf(info6), "\n")
    })
-    
+
 #     info <- reactive({
 #         info1 <- paste("This analysis was conducted with ", strsplit(R.version$version.string, " \\(")[[1]][1], ".", sep = "")
 #         info2 <- paste("It was executed on ", date(), ".", sep = "")
@@ -206,47 +206,47 @@ shinyServer(function(input, output) {
 #     })
     output$info.cfa <- renderPrint({
       info()
-    })    
+    })
     output$info.gcm <- renderPrint({
         info()
     })
-    
+
     output$info.sem <- renderPrint({
       info()
     })
-    
+
     output$textareacfa <- renderPrint({
       bscfa()
     })
-    
+
     output$textareagcm <- renderPrint({
         bsgcm()
     })
-    
+
     output$textareasem <- renderPrint({
       bssem()
     })
 
     output$correl.cfa <- renderPrint({
       correl.cfa()
     })
-    
+
     output$correl.gcm <- renderPrint({
         correl.gcm()
     })
-    
+
     output$correl.sem <- renderPrint({
       correl.sem()
     })
-    
+
     output$result.cfa <- renderPrint({
       result.cfa()
     })
-    
+
     output$result.gcm <- renderPrint({
         result.gcm()
     })
-    
+
     output$result.sem <- renderPrint({
       result.sem()
     })