diff --git a/R/glmClassical.R b/R/glmClassical.R
index 1e757278..3e569508 100644
--- a/R/glmClassical.R
+++ b/R/glmClassical.R
@@ -189,10 +189,15 @@ GeneralizedLinearModel <- function(jaspResults, dataset = NULL, options, ...) {
     glmModels <- .glmComputeModel(jaspResults, dataset, options)
     hasNuisance <- .hasNuisance(options)
     if (hasNuisance) {
-      terms <- rownames(coef(summary(glmModels[["nullModel"]])))
-      terms <- jaspBase::gsubInteractionSymbol(terms[terms!="(Intercept)"])
-      message <- gettextf("Null model contains nuisance parameters: %s",
-                          paste(terms, collapse = ", "))
+      if ((options[["family"]] == "other") & (options[["otherGlmModel"]] %in% c("multinomialLogistic", "ordinalLogistic")))
+        termsNullModel <- rownames(VGAM::coef(VGAM::summaryvglm(glmModels[["nullModel"]])))
+      else if (options[["otherGlmModel"]] == "firthLogistic")
+        termsNullModel <- names(coef((glmModels[["nullModel"]])))
+      else
+        termsNullModel <- rownames(coef(summary(glmModels[["nullModel"]])))
+      nuisanceTerms <- jaspBase::gsubInteractionSymbol(termsNullModel[!grepl("(Intercept)", termsNullModel, fixed = TRUE)])
+      message <- gettextf("Null model contains nuisance parameters: %s.",
+                          paste(nuisanceTerms, collapse = ", "))
       jaspResults[["modelSummary"]]$addFootnote(message)
     }
 
@@ -223,17 +228,17 @@ GeneralizedLinearModel <- function(jaspResults, dataset = NULL, options, ...) {
         pValue       <- 1 - pchisq(chiValue, glmModels[["fullModel"]][["df"]])
       }
       else {
-        devNullModel <- deviance(glmModels[["nullModel"]])
-        aicNullModel <- AIC(glmModels[["nullModel"]])
-        bicNullModel <- BIC(glmModels[["nullModel"]])
-        dofNullModel <- df.residual(glmModels[["nullModel"]])
+        devNullModel <- VGAM::deviance(glmModels[["nullModel"]])
+        aicNullModel <- VGAM::AIC(glmModels[["nullModel"]])
+        bicNullModel <- VGAM::BIC(glmModels[["nullModel"]])
+        dofNullModel <- VGAM::df.residual(glmModels[["nullModel"]])
 
-        devFullModel <- deviance(glmModels[["fullModel"]])
-        aicFullModel <- AIC(glmModels[["fullModel"]])
-        bicFullModel <- BIC(glmModels[["fullModel"]])
-        dofFullModel <- df.residual(glmModels[["fullModel"]])
+        devFullModel <- VGAM::deviance(glmModels[["fullModel"]])
+        aicFullModel <- VGAM::AIC(glmModels[["fullModel"]])
+        bicFullModel <- VGAM::BIC(glmModels[["fullModel"]])
+        dofFullModel <- VGAM::df.residual(glmModels[["fullModel"]])
 
-        anovaRes     <- anova(glmModels[["nullModel"]], glmModels[["fullModel"]], type = 1)
+        anovaRes     <- VGAM::anova.vglm(glmModels[["nullModel"]], glmModels[["fullModel"]], type = 1)
         chiValue     <- devNullModel - devFullModel
         pValue       <- anovaRes[["Pr(>Chi)"]][[2]]
       }
diff --git a/R/glmCommonFunctions.R b/R/glmCommonFunctions.R
index be799579..afe2104e 100644
--- a/R/glmCommonFunctions.R
+++ b/R/glmCommonFunctions.R
@@ -89,22 +89,22 @@
       fullModel <- VGAM::vglm(ff,
                               family = VGAM::multinomial(),
                               data = dataset,
-                              weights = .getWeightVariable(options$weights))
+                              weights = eval(.getWeightVariable(options$weights)))
       nullModel <- VGAM::vglm(nf,
                               family = VGAM::multinomial(),
                               data = dataset,
-                              weights = .getWeightVariable(options$weights))
+                              weights = eval(.getWeightVariable(options$weights)))
     }
 
     if (options$otherGlmModel == "ordinalLogistic") {
       fullModel <- VGAM::vglm(ff,
                               family = VGAM::cumulative(link = "logitlink", parallel = TRUE),
                               data = dataset,
-                              weights = .getWeightVariable(options$weights))
+                              weights = eval(.getWeightVariable(options$weights)))
       nullModel <- VGAM::vglm(nf,
                               family = VGAM::cumulative(link = "logitlink", parallel = TRUE),
                               data = dataset,
-                              weights = .getWeightVariable(options$weights))
+                              weights = eval(.getWeightVariable(options$weights)))
     }
 
     if (options$otherGlmModel == "firthLogistic") {
@@ -112,12 +112,12 @@
                                     data = dataset,
                                     pl = TRUE,
                                     firth = TRUE,
-                                    weights = .getWeightVariable(options$weights))
+                                    weights = eval(.getWeightVariable(options$weights)))
       nullModel <- logistf::logistf(nf,
                                     data = dataset,
                                     pl = TRUE,
                                     firth = TRUE,
-                                    weights = .getWeightVariable(options$weights))
+                                    weights = eval(.getWeightVariable(options$weights)))
     }
   }
 
diff --git a/inst/qml/common/GlmInputComponent.qml b/inst/qml/common/GlmInputComponent.qml
index e2fb6718..4295706e 100644
--- a/inst/qml/common/GlmInputComponent.qml
+++ b/inst/qml/common/GlmInputComponent.qml
@@ -24,7 +24,7 @@ import JASP				1.0
 
 // All Analysis forms must be built with the From QML item
 Group {
-	property bool otherFamilyNotSelected: family.currentValue !== "other"
+	property bool otherFamilyNotSelected: family.currentValue !== "other";
 
 	VariablesForm
 	{
@@ -39,7 +39,7 @@ Group {
 		{
 			name:				"dependent"
 			title:				qsTr("Dependent variable")
-			allowedColumns:		["scale","ordinal", "nominal", "nominalText"]
+			allowedColumns:		["scale", "ordinal", "nominal", "nominalText"]
 			singleVariable:		true
 		}