Update wrappers

jasp-stats · Nov 5, 2024 · b9ded77 · b9ded77
1 parent 0550600
commit b9ded77
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Showing 9 changed files with 43 additions and 57 deletions.
diff --git a/R/correlationWrapper.R b/R/correlationWrapper.R
@@ -1,5 +1,5 @@
 #
-# Copyright (C) 2013-2022 University of Amsterdam
+# Copyright (C) 2013-2024 University of Amsterdam
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
@@ -19,7 +19,7 @@
 
 Correlation <- function(
           data = NULL,
-          version = "0.19",
+          version = "0.19.2",
           alternative = "twoSided",
           assumptionCheckMultivariateEnergy = FALSE,
           assumptionCheckMultivariateMardia = FALSE,
@@ -41,7 +41,7 @@ Correlation <- function(
           meansAndSd = FALSE,
           naAction = "pairwise",
           pairwiseDisplay = FALSE,
-          partialOutVariables = list(),
+          partialOutVariables = list(types = list(), value = NULL),
           pearson = TRUE,
           plotHeight = 320,
           plotWidth = 480,
@@ -56,7 +56,7 @@ Correlation <- function(
           significanceFlagged = FALSE,
           significanceReport = TRUE,
           spearman = FALSE,
-          variables = list(),
+          variables = list(types = list(), value = NULL),
           vovkSellke = FALSE) {
 
    defaultArgCalls <- formals(jaspRegression::Correlation)

diff --git a/R/correlationbayesianWrapper.R b/R/correlationbayesianWrapper.R
@@ -1,5 +1,5 @@
 #
-# Copyright (C) 2013-2022 University of Amsterdam
+# Copyright (C) 2013-2024 University of Amsterdam
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
@@ -19,7 +19,7 @@
 
 CorrelationBayesian <- function(
           data = NULL,
-          version = "0.19",
+          version = "0.19.2",
           alternative = "twoSided",
           bayesFactorReport = TRUE,
           bayesFactorType = "BF10",
@@ -52,7 +52,7 @@ CorrelationBayesian <- function(
           spearman = FALSE,
           supportCorrelationFlagged = FALSE,
           variablePairs = list(),
-          variables = list()) {
+          variables = list(types = list(), value = NULL)) {
 
    defaultArgCalls <- formals(jaspRegression::CorrelationBayesian)
    defaultArgs <- lapply(defaultArgCalls, eval)

diff --git a/R/generalizedlinearmodelWrapper.R b/R/generalizedlinearmodelWrapper.R
@@ -1,5 +1,5 @@
 #
-# Copyright (C) 2013-2022 University of Amsterdam
+# Copyright (C) 2013-2024 University of Amsterdam
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
@@ -19,23 +19,23 @@
 
 GeneralizedLinearModel <- function(
           data = NULL,
-          version = "0.19",
+          version = "0.19.2",
           formula = NULL,
           isNuisance = NULL,
           coefficientCi = FALSE,
           coefficientCiLevel = 0.95,
           coefficientEstimate = TRUE,
           contrasts = list(),
           covarianceRatio = FALSE,
-          covariates = list(),
-          dependent = "",
+          covariates = list(types = list(), value = NULL),
+          dependent = list(types = list(), value = ""),
           devianceGoodnessOfFit = FALSE,
           devianceResidualQqPlot = FALSE,
           devianceResidualVsFittedPlot = FALSE,
           devianceResidualVsPredictorPlot = FALSE,
           dfbetas = FALSE,
           dffits = FALSE,
-          factors = list(),
+          factors = list(types = list(), value = NULL),
           family = "bernoulli",
           interceptTerm = TRUE,
           leverage = FALSE,
@@ -49,9 +49,9 @@ GeneralizedLinearModel <- function(
           marginalMeansPAdjustment = "holm",
           marginalMeansResponse = TRUE,
           marginalMeansSd = 1,
-          marginalMeansVars = list(),
-          modelTerms = list(),
-          offset = "",
+          marginalMeansVars = list(types = list(), value = NULL),
+          modelTerms = list(optionKey = "components", types = list(), value = list()),
+          offset = list(types = list(), value = ""),
           otherGlmModel = "multinomialLogistic",
           partialResidualPlot = FALSE,
           pearsonGoodnessOfFit = FALSE,
@@ -80,7 +80,7 @@ GeneralizedLinearModel <- function(
           studentizedResidualOutlierTableTopN = 3,
           tolerance = FALSE,
           vif = FALSE,
-          weights = "",
+          weights = list(types = list(), value = ""),
           workingResponseVsLinearPredictorPlot = FALSE) {
 
    defaultArgCalls <- formals(jaspRegression::GeneralizedLinearModel)

diff --git a/R/regressionlinearWrapper.R b/R/regressionlinearWrapper.R
@@ -1,5 +1,5 @@
 #
-# Copyright (C) 2013-2022 University of Amsterdam
+# Copyright (C) 2013-2024 University of Amsterdam
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
@@ -19,7 +19,7 @@
 
 RegressionLinear <- function(
           data = NULL,
-          version = "0.19",
+          version = "0.19.2",
           formula = NULL,
           isNuisance = NULL,
           coefficientBootstrap = FALSE,
@@ -31,13 +31,13 @@ RegressionLinear <- function(
           collinearityStatistic = FALSE,
           covarianceMatrix = FALSE,
           covarianceRatio = FALSE,
-          covariates = list(),
-          dependent = "",
+          covariates = list(types = list(), value = NULL),
+          dependent = list(types = list(), value = ""),
           descriptives = FALSE,
           dfbetas = FALSE,
           dffits = FALSE,
           fChange = FALSE,
-          factors = list(),
+          factors = list(types = list(), value = NULL),
           interceptTerm = TRUE,
           leverage = FALSE,
           mahalanobis = FALSE,
@@ -49,7 +49,7 @@ RegressionLinear <- function(
           method = "enter",
           modelAICBIC = FALSE,
           modelFit = TRUE,
-          modelTerms = list(list(components = list(), name = "model0", title = "Model 0"), list(components = list(), name = "model1", title = "Model 1")),
+          modelTerms = list(list(components = list(), name = "model0", title = "Model 0", types = list()), list(components = list(), name = "model1", title = "Model 1", types = list())),
           naAction = "listwise",
           nested = TRUE,
           partAndPartialCorrelation = FALSE,
@@ -81,7 +81,7 @@ RegressionLinear <- function(
           steppingMethodCriteriaPRemoval = 0.1,
           steppingMethodCriteriaType = "pValue",
           vovkSellke = FALSE,
-          weights = "") {
+          weights = list(types = list(), value = "")) {
 
    defaultArgCalls <- formals(jaspRegression::RegressionLinear)
    defaultArgs <- lapply(defaultArgCalls, eval)

diff --git a/R/regressionlinearbayesianWrapper.R b/R/regressionlinearbayesianWrapper.R
@@ -1,5 +1,5 @@
 #
-# Copyright (C) 2013-2022 University of Amsterdam
+# Copyright (C) 2013-2024 University of Amsterdam
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
@@ -19,7 +19,7 @@
 
 RegressionLinearBayesian <- function(
           data = NULL,
-          version = "0.19",
+          version = "0.19.2",
           formula = NULL,
           isNuisance = NULL,
           bayesFactorOrder = "bestModelTop",
@@ -28,8 +28,8 @@ RegressionLinearBayesian <- function(
           betaBinomialParamA = 1,
           betaBinomialParamB = 1,
           castilloParamU = 1,
-          covariates = list(),
-          dependent = "",
+          covariates = list(types = list(), value = NULL),
+          dependent = list(types = list(), value = ""),
           descriptives = FALSE,
           effectsType = "allModels",
           gPriorAlpha = 3,
@@ -40,7 +40,7 @@ RegressionLinearBayesian <- function(
           modelComplexityPlot = FALSE,
           modelPrior = "betaBinomial",
           modelProbabilitiesPlot = FALSE,
-          modelTerms = list(),
+          modelTerms = list(optionKey = "components", types = list(), value = list()),
           modelsShown = "limited",
           numModelsShown = 10,
           numberOfModels = 0,
@@ -63,7 +63,7 @@ RegressionLinearBayesian <- function(
           seed = 1,
           setSeed = FALSE,
           summaryType = "averaged",
-          weights = "",
+          weights = list(types = list(), value = ""),
           wilsonParamLambda = 1) {
 
    defaultArgCalls <- formals(jaspRegression::RegressionLinearBayesian)

diff --git a/R/regressionlogisticWrapper.R b/R/regressionlogisticWrapper.R
@@ -1,5 +1,5 @@
 #
-# Copyright (C) 2013-2022 University of Amsterdam
+# Copyright (C) 2013-2024 University of Amsterdam
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
@@ -19,7 +19,7 @@
 
 RegressionLogistic <- function(
           data = NULL,
-          version = "0.19",
+          version = "0.19.2",
           formula = NULL,
           isNuisance = NULL,
           accuracy = FALSE,
@@ -37,13 +37,13 @@ RegressionLogistic <- function(
           conditionalEstimatePlotPoints = FALSE,
           confusionMatrix = FALSE,
           covarianceRatio = FALSE,
-          covariates = list(),
-          dependent = "",
+          covariates = list(types = list(), value = NULL),
+          dependent = list(types = list(), value = ""),
           descriptives = FALSE,
           dfbetas = FALSE,
           dffits = FALSE,
           fMeasure = FALSE,
-          factors = list(),
+          factors = list(types = list(), value = NULL),
           hMeasure = FALSE,
           independentVsPredictedPlot = FALSE,
           independentVsPredictedPlotIncludeInteractions = TRUE,
@@ -52,7 +52,7 @@ RegressionLogistic <- function(
           leverage = FALSE,
           mahalanobis = FALSE,
           method = "enter",
-          modelTerms = list(list(components = list(), name = "model0", title = "Model 0"), list(components = list(), name = "model1", title = "Model 1")),
+          modelTerms = list(list(components = list(), name = "model0", title = "Model 0", types = list()), list(components = list(), name = "model1", title = "Model 1", types = list())),
           multicollinearity = FALSE,
           nested = TRUE,
           oddsRatio = FALSE,
@@ -80,7 +80,7 @@ RegressionLogistic <- function(
           specificity = FALSE,
           squaredPearsonResidualVsFittedPlot = FALSE,
           vovkSellke = FALSE,
-          weights = "") {
+          weights = list(types = list(), value = "")) {
 
    defaultArgCalls <- formals(jaspRegression::RegressionLogistic)
    defaultArgs <- lapply(defaultArgCalls, eval)

diff --git a/R/regressionlogisticbayesianWrapper.R b/R/regressionlogisticbayesianWrapper.R
@@ -1,5 +1,5 @@
 #
-# Copyright (C) 2013-2022 University of Amsterdam
+# Copyright (C) 2013-2024 University of Amsterdam
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
@@ -19,7 +19,7 @@
 
 RegressionLogisticBayesian <- function(
           data = NULL,
-          version = "0.19",
+          version = "0.19.2",
           bayesFactorOrder = "bestModelTop",
           bayesFactorType = "BF10",
           bernoulliParam = 0.5,
@@ -29,19 +29,19 @@ RegressionLogisticBayesian <- function(
           cchPriorAlpha = 0.5,
           cchPriorBeta = 2,
           cchPriorS = 0,
-          covariates = list(),
-          dependent = "",
+          covariates = list(types = list(), value = NULL),
+          dependent = list(types = list(), value = ""),
           descriptives = FALSE,
           effectsType = "allModels",
-          factors = list(),
+          factors = list(types = list(), value = NULL),
           gPriorAlpha = 3,
           inclusionProbabilitiesPlot = FALSE,
           logPosteriorOddsPlot = FALSE,
           marginalPosteriorPlot = FALSE,
           modelComplexityPlot = FALSE,
           modelPrior = "betaBinomial",
           modelProbabilitiesPlot = FALSE,
-          modelTerms = list(),
+          modelTerms = list(optionKey = "components", types = list(), value = list()),
           modelsShown = "limited",
           numModelsShown = 10,
           numberOfModels = 0,
@@ -64,7 +64,7 @@ RegressionLogisticBayesian <- function(
           seed = 1,
           setSeed = FALSE,
           summaryType = "averaged",
-          weights = "",
+          weights = list(types = list(), value = ""),
           wilsonParamLambda = 1) {
 
    defaultArgCalls <- formals(jaspRegression::RegressionLogisticBayesian)

diff --git a/inst/qml/RegressionLinear.qml b/inst/qml/RegressionLinear.qml
@@ -27,13 +27,6 @@ Form
 	property int analysis:	Common.Type.Analysis.LinearRegression
 	property int framework:	Common.Type.Framework.Classical
 
-	Formula
-	{
-		lhs: "dependent"
-		rhs: [{ name: "modelTerms", extraOptions: "isNuisance" }]
-		userMustSpecify: "covariates"
-	}
-
 	VariablesForm
 	{
 		AvailableVariablesList { name: "allVariablesList" }

diff --git a/inst/qml/RegressionLogistic.qml b/inst/qml/RegressionLogistic.qml
@@ -25,13 +25,6 @@ Form
 	plotWidth: 480
 	plotHeight: 320
 
-	Formula
-	{
-		lhs: "dependent"
-		rhs: [{ name: "modelTerms", extraOptions: "isNuisance" }]
-		userMustSpecify: "covariates"
-	}
-
 	VariablesForm
 	{
 		AvailableVariablesList { name: "allVariablesList" }