#
# 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
RegressionLogistic <- function(
data = NULL,
version = "0.18.2",
formula = NULL,
isNuisance = NULL,
accuracy = FALSE,
auc = FALSE,
brierScore = FALSE,
coefficientBootstrap = FALSE,
coefficientBootstrapSamples = 5000,
coefficientCi = FALSE,
coefficientCiAsOddsRatio = FALSE,
coefficientCiLevel = 0.95,
coefficientEstimate = TRUE,
coefficientStandardized = FALSE,
conditionalEstimatePlot = FALSE,
conditionalEstimatePlotCi = 0.95,
conditionalEstimatePlotPoints = FALSE,
confusionMatrix = FALSE,
covariates = list(),
dependent = "",
descriptives = FALSE,
fMeasure = FALSE,
factors = list(),
hMeasure = FALSE,
interceptTerm = TRUE,
method = "enter",
modelTerms = list(),
multicollinearity = FALSE,
oddsRatio = FALSE,
plotHeight = 320,
plotWidth = 480,
precision = FALSE,
precisionRecallPlot = FALSE,
precisionRecallPlotCutoffLabel = FALSE,
precisionRecallPlotCutoffStep = 0.2,
residualCasewiseDiagnostic = FALSE,
residualCasewiseDiagnosticCooksDistanceThreshold = 1,
residualCasewiseDiagnosticType = "residualZ",
residualCasewiseDiagnosticZThreshold = 3,
residualType = "deviance",
residualVsFittedPlot = FALSE,
residualVsPredictorPlot = FALSE,
robustSe = FALSE,
rocPlot = FALSE,
rocPlotCutoffLabel = FALSE,
rocPlotCutoffStep = 0.2,
sensitivity = FALSE,
specificity = FALSE,
squaredPearsonResidualVsFittedPlot = FALSE,
vovkSellke = FALSE,
weights = "") {
defaultArgCalls <- formals(jaspRegression::RegressionLogistic)
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("isNuisance", "covariates", "dependent", "factors", "method", "modelTerms", "weights")
for (name in optionsWithFormula) {
if ((name %in% optionsWithFormula) && inherits(options[[name]], "formula")) options[[name]] = jaspBase::jaspFormula(options[[name]], data) }
return(jaspBase::runWrappedAnalysis("jaspRegression::RegressionLogistic", data, options, version))
}
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