#
# Copyright (C) 2013-2022 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
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# This is a generated file. Don't change it
Anova <- function(
data = NULL,
version = "0.19",
formula = NULL,
applyMoreyCorrectionErrorBars = TRUE,
barPlotCiInterval = 0.95,
barPlotErrorBarType = "ci",
barPlotErrorBars = FALSE,
barPlotHorizontalAxis = "",
barPlotHorizontalZeroFix = TRUE,
barPlotSeparatePlots = "",
contrastCi = FALSE,
contrastCiLevel = 0.95,
contrastEffectSize = FALSE,
contrasts = list(),
customContrasts = list(),
dependent = "",
descriptivePlotCiLevel = 0.95,
descriptivePlotErrorBar = FALSE,
descriptivePlotErrorBarType = "ci",
descriptivePlotHorizontalAxis = "",
descriptivePlotSeparateLines = "",
descriptivePlotSeparatePlot = "",
descriptives = FALSE,
effectSizeCi = FALSE,
effectSizeCiLevel = 0.95,
effectSizeEstimates = FALSE,
effectSizeEtaSquared = FALSE,
effectSizeGeneralEtaSquared = FALSE,
effectSizeOmegaSquared = TRUE,
effectSizePartialEtaSquared = FALSE,
effectSizePartialOmegaSquared = FALSE,
fixedFactors = list(),
homogeneityCorrectionBrown = FALSE,
homogeneityCorrectionNone = TRUE,
homogeneityCorrectionWelch = FALSE,
homogeneityTests = FALSE,
kruskalCiLevel = 0.95,
kruskalEffectSizeEstimates = FALSE,
kruskalEpsilon = TRUE,
kruskalEta = FALSE,
kruskalWallisFactors = list(),
marginalMeanBootstrap = FALSE,
marginalMeanBootstrapSamples = 1000,
marginalMeanCiCorrection = "none",
marginalMeanComparedToZero = FALSE,
marginalMeanTerms = list(),
modelTerms = list(),
plotHeight = 320,
plotHeightDescriptivesPlotLegend = 300,
plotHeightDescriptivesPlotNoLegend = 300,
plotHeightQQPlot = 300,
plotWidth = 480,
plotWidthDescriptivesPlotLegend = 430,
plotWidthDescriptivesPlotNoLegend = 350,
plotWidthQQPlot = 300,
postHocCi = FALSE,
postHocCiLevel = 0.95,
postHocConditionalTable = FALSE,
postHocCorrectionBonferroni = FALSE,
postHocCorrectionHolm = FALSE,
postHocCorrectionScheffe = FALSE,
postHocCorrectionSidak = FALSE,
postHocCorrectionTukey = TRUE,
postHocLetterAlpha = 0.05,
postHocLetterTable = FALSE,
postHocSignificanceFlag = FALSE,
postHocTerms = list(),
postHocTypeDunn = FALSE,
postHocTypeDunnet = FALSE,
postHocTypeGames = FALSE,
postHocTypeStandard = TRUE,
postHocTypeStandardBootstrap = FALSE,
postHocTypeStandardBootstrapSamples = 1000,
postHocTypeStandardEffectSize = FALSE,
qqPlot = FALSE,
rainCloudHorizontalAxis = "",
rainCloudHorizontalDisplay = FALSE,
rainCloudSeparatePlots = "",
rainCloudYAxisLabel = "",
randomFactors = list(),
restrictedAvailableCoefficients = FALSE,
restrictedBootstrap = FALSE,
restrictedBootstrapCiLevel = 0.95,
restrictedBootstrapSamples = 1000,
restrictedHeterogeneityCorrection = "none",
restrictedInformedHypothesisTestForAllModels = FALSE,
restrictedInterceptInclusion = FALSE,
restrictedMarginalMeanForAllModels = FALSE,
restrictedMarginalMeanTerms = list(),
restrictedModelComparison = "complement",
restrictedModelComparisonCoefficients = FALSE,
restrictedModelComparisonCoefficientsHighlight = TRUE,
restrictedModelComparisonMatrix = FALSE,
restrictedModelComparisonReference = "Model 1",
restrictedModelComparisonWeights = TRUE,
restrictedModelSummaryForAllModels = FALSE,
restrictedModels = list(list(informedHypothesisTest = FALSE, marginalMean = FALSE, name = "Model 1", summary = FALSE, syntax = "")),
simpleMainEffectFactor = "",
simpleMainEffectModeratorFactorOne = "",
simpleMainEffectModeratorFactorTwo = "",
sumOfSquares = "type3",
vovkSellke = FALSE,
wlsWeights = "") {
defaultArgCalls <- formals(jaspAnova::Anova)
defaultArgs <- lapply(defaultArgCalls, eval)
options <- as.list(match.call())[-1L]
options <- lapply(options, eval)
defaults <- setdiff(names(defaultArgs), names(options))
options[defaults] <- defaultArgs[defaults]
options[["data"]] <- NULL
options[["version"]] <- NULL
if (!is.null(formula)) {
if (!inherits(formula, "formula")) {
formula <- as.formula(formula)
}
options$formula <- jaspBase::jaspFormula(formula, data)
}
optionsWithFormula <- c("barPlotHorizontalAxis", "barPlotSeparatePlots", "contrasts", "customContrasts", "dependent", "descriptivePlotHorizontalAxis", "descriptivePlotSeparateLines", "descriptivePlotSeparatePlot", "fixedFactors", "kruskalWallisFactors", "marginalMeanCiCorrection", "marginalMeanTerms", "modelTerms", "postHocTerms", "rainCloudHorizontalAxis", "rainCloudSeparatePlots", "randomFactors", "restrictedHeterogeneityCorrection", "restrictedMarginalMeanTerms", "restrictedModelComparison", "restrictedModelComparisonReference", "restrictedModels", "simpleMainEffectFactor", "simpleMainEffectModeratorFactorOne", "simpleMainEffectModeratorFactorTwo", "sumOfSquares", "wlsWeights")
for (name in optionsWithFormula) {
if ((name %in% optionsWithFormula) && inherits(options[[name]], "formula")) options[[name]] = jaspBase::jaspFormula(options[[name]], data) }
return(jaspBase::runWrappedAnalysis("jaspAnova::Anova", data, options, version))
}
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