Fix output for nonconverged models

jasp-stats · Oct 10, 2023 · 82bec3b · 82bec3b
1 parent 4a172ff
commit 82bec3b
Showing 1 changed file with 13 additions and 5 deletions.
diff --git a/R/classicProcess.R b/R/classicProcess.R
@@ -915,7 +915,7 @@ procModelGraphSingleModel <- function(modelOptions, globalDependent, options) {
 # Output functions ----
 .procFilterFittedModels <- function(procResults) {
   isFitted <- sapply(procResults, function(mod) {
-    if (!is.null(mod) && !is.character(mod))
+    if (!is.null(mod) && !is.character(mod) && mod@Fit@converged)
       return(mod@Options[["do.fit"]])
     return(FALSE)
   })
@@ -979,6 +979,13 @@ procModelGraphSingleModel <- function(modelOptions, globalDependent, options) {
   if (!is.null(jaspResults[["modelSummaryTable"]])) return()
 
   procResults <- lapply(options[["processModels"]], function(mod) modelsContainer[[mod[["name"]]]][["fittedModel"]]$object)
+
+  converged <- sapply(procResults, function(mod) mod@Fit@converged)
+
+  if (!all(converged)) {
+    summaryTable$addFootnote(message = gettext("At least one model did not converge."))
+  }
+
   procResults <- .procFilterFittedModels(procResults)
 
   summaryTable <- createJaspTable(title = gettext("Model summary"))
@@ -1012,7 +1019,7 @@ procModelGraphSingleModel <- function(modelOptions, globalDependent, options) {
     summaryTable$setError(errmsg)
   }
 
-  if (length(procResults) == 0) return()
+  modelNames <- sapply(options[["processModels"]], function(mod) mod[["name"]])
 
   modelNumbers <- lapply(options[["processModels"]], function(mod) {
     if (mod[["inputType"]] == "inputModelNumber") {
@@ -1025,14 +1032,15 @@ procModelGraphSingleModel <- function(modelOptions, globalDependent, options) {
     return(.procRecognizeModelNumber(modelsContainer[[mod[["name"]]]][["graph"]]$object))
   })
 
-  modelNames <- sapply(options[["processModels"]], function(mod) mod[["name"]])
+  summaryTable[["Model"]]       <- modelNames
+  summaryTable[["modelNumber"]] <- modelNumbers
+
+  if (length(procResults) == 0) return()
 
   aic <- sapply(procResults, AIC)
   bic <- sapply(procResults, BIC)
   df  <- sapply(procResults, lavaan::fitMeasures, fit.measures = "df")
 
-  summaryTable[["Model"]]    <- modelNames
-  summaryTable[["modelNumber"]] <- modelNumbers
   summaryTable[["AIC"]]      <- aic
   summaryTable[["BIC"]]      <- bic
   summaryTable[["logLik"]]   <- sapply(procResults, lavaan::logLik)