Function reference • userfriendlyscience

All functions
`areColors()`	Check whether elements of a vector are valid colors
`associationMatrix()`	associationMatrix
`computeStatistic_t()` `computeStatistic_r()` `computeStatistic_f()` `computeStatistic_chisq()` `computeEffectSize_d()` `computeEffectSize_r()` `computeEffectSize_etasq()` `computeEffectSize_omegasq()` `computeEffectSize_v()`	associationMatrix Helper Functions
`associationsDiamondPlot()` `associationsToDiamondPlotDf()`	A diamondplot with confidence intervals for associations
`asymmetricalScatterMatrix()`	asymmetricalScatterMatrix
`averageFishersZs()`	averageFishersZs
`averagePearsonRs()`	averagePearsonRs
`getData()` `getDat()` `exportToSPSS()` `filterBy()` `useAll()` `mediaan()` `modus()`	Basic SPSS translation functions
`biAxisDiamondPlot()`	Diamondplot with two Y axes
`checkDataIntegrity()`	Conveniently checking data integrity
`CIBER()` `detStructCIBER()`	Confidence Interval-Based Estimation of Relevance (CIBER)
`dd()` `pd()` `qd()` `rd()` `dCohensd()` `pCohensd()` `qCohensd()` `rCohensd()` `pdExtreme()` `pdMild()` `pdInterval()` `cohensdCI()` `confIntD()` `pwr.cohensdCI()` `pwr.confIntd()`	The distribution of Cohen's d
`confIntOmegaSq()`	Confidence intervals for Omega Squared
`confIntProp()`	Confidence intervals for proportions, vectorized over all arguments
`confIntR()`	A function to compute a correlation's confidence interval
`crossTab()` `cramersV()` `confIntV()`	crossTab, confIntV and cramersV
`convert.d.to.nnc()` `convert.d.to.eer()`	Helper functions for Numbers Needed for Change
`convert.b.to.t()` `convert.chisq.to.p()` `convert.chisq.to.V()` `convert.cohensf.to.omegasq()` `convert.cohensfsq.to.omegasq()` `convert.d.to.logodds()` `convert.d.to.r()` `convert.d.to.t()` `convert.d.to.variance()` `convert.etasq.to.cohensf()` `convert.f.to.etasq()` `convert.f.to.omegasq()` `convert.f.to.p()` `convert.f.to.d()` `convert.fisherz.to.r()` `convert.logodds.to.d()` `convert.logodds.to.r()` `convert.means.to.d()` `convert.ncf.to.omegasq()` `convert.omegasq.to.cohensf()` `convert.omegasq.to.cohensfsq()` `convert.omegasq.to.f()` `convert.or.to.d()` `convert.or.to.r()` `convert.percentage.to.se()` `convert.r.to.t()` `convert.r.to.d()` `convert.r.to.p()` `convert.r.to.fisherz()` `convert.t.to.r()` `convert.t.to.d()` `convert.t.to.p()`	conversion functions
`createSigma()`	createSigma: convenience function for mvrnorm
`curfnfinder()`	Function to find the name of the calling function
`descr()`	descr (or descriptives)
`detectRareWords()` `textToWords()`	Looking up word frequencies
`determinantStructure()` `determinantVar()` `subdeterminants()` `subdeterminantProducts()` `print(<determinantStructure>)` `plot(<determinantStructure>)`	Determinant Structure specification
`detStructAddVarLabels()` `detStructAddVarNames()` `detStructComputeProducts()` `detStructComputeScales()`	Functions to preprocess determinant structures
`diamondPlot()`	Basic diamond plot construction function
`didacticPlot()` `didacticPlotTheme()`	didacticPlot
`dlvPlot()` `dlvTheme()`	dlvPlot
`escapeRegex()`	Escapes any characters that would have special meaning in a reqular expression.
`examine()` `examineBy()`	Examine one or more variables
`exceptionalScore()`	exceptionalScore
`exceptionalScores()`	exceptionalScores
`extractVarName()`	Extract variable names
`facComAnalysis()`	Wrapper for psych's factor analysis and principal components analysis functions
`faConfInt()`	Extract confidence bounds from psych's factor analysis object
`factorLoadingDiamondCIplot()`	Two-dimensional visualisation of factor analyses
`fanova()`	Flexible anova
`findShortestInterval()`	Find the shortest interval
`formatCI()`	Pretty formatting of confidence intervals
`freq()` `frequencies()`	Frequency tables
`fullFact()`	fullFact
`genlog()`	Generalized Logistic Analysis
`genlogFunction()`	Generalized Logistic Function
`ggBarChart()`	Bar chart using ggplot
`ggBoxplot()`	Box plot using ggplot
`ggConfidenceCurve()`	Confidence Curves
`ggDiamondLayer()` `diamondCoordinates()` `varsToDiamondPlotDf()` `rawDataDiamondLayer()`	Basic ggplot2 diamond plot layer construction functions
`ggEasyRidge()` `ggEasyBar()`	Convenience functions for ggplots based on multiple variables
`erDataSeq()` `ggNNC()` `convert.threshold.to.er()` `convert.er.to.threshold()`	Visualising Numbers Needed for Change
`ggPie()`	A ggplot pie chart
`ggProportionPlot()`	Sample distribution based plotting of proportions
`ggqq()`	Easy ggplot Q-Q plot
`importLimeSurveyData()`	importLimeSurveyData
`invertItems()`	invertItems
`iqrOutlier()`	Identify outliers according to the IQR criterion
`is.nr()`	is.nr
`isTrue()`	isTrue
`itemInspection()`	itemInspection
`knitFig()`	Easily knit a custom figure fragment
`logRegr()`	Userfriendly wrapper to do logistic regression in R
`meanDiff.multi()`	meanDiff.multi
`meanDiff()`	meanDiff
`meansComparisonDiamondPlot()` `duoComparisonDiamondPlot()`	meansComparisonDiamondPlot and duoComparisonDiamondPlot
`meansDiamondPlot()`	Diamond plots
`meanSDtoDiamondPlot()`	A diamond plot based on means, standard deviations, and sample sizes
`multiResponse()`	Generate a table for multiple response questions
`multiVarFreq()`	Generate a table collapsing frequencies of multiple variables
`nnc()`	Numbers Needed for Change
`normalityAssessment()` `samplingDistribution()` `dataShape()`	normalityAssessment and samplingDistribution
`oddsratio()`	oddsratio
`domegaSq()` `pomegaSq()` `qomegaSq()` `romegaSq()`	The distribution of Omega Squared
`oneway()`	oneway
`paginatedAsymmetricalScatterMatrix()`	paginatedAsymmetricalScatterMatrix
`pander(<freq>)` `pander(<meanDiff>)` `pander(<normalityAssessment>)` `pander(<dataShape>)` `pander(<associationMatrix>)` `pander(<crossTab>)` `pander(<oneway>)` `pander(<regr>)` `pander(<descr>)` `pander(<examine>)` `pander(<examineBy>)` `pander(<frequencies>)`	userfriendlyscience methods to pander objects
`piecewiseRegr()`	Piecewise regression analysis
`posthocTGH()`	posthocTGH
`powerHist()`	powerHist
`prevalencePower()`	Power analysis for establishing a prevalence
`print(<dlvPlot>)` `print(<freq>)` `print(<meanConfInt>)` `print(<meanDiff>)` `print(<meanDiff.multi>)` `print(<normalityAssessment>)` `print(<oddsratio>)` `print(<powerHist>)` `print(<rMatrix>)` `print(<scaleDiagnosis>)` `print(<scaleStructure>)` `print(<sdConfInt>)` `print(<testRetestAlpha>)` `print(<testRetestCES>)` `print(<testRetestReliability>)` `print(<parallelSubscales>)` `print(<dataShape>)` `print(<didacticPlot>)` `print(<scatterMatrix>)` `print(<CramersV>)` `print(<associationMatrix>)` `print(<confIntV>)` `print(<cohensdCI>)` `print(<crossTab>)` `print(<oneway>)` `print(<posthocTGH>)` `print(<scaleInspection>)` `print(<regr>)` `print(<processOpenSesameIAT>)` `print(<processOpenSesameIAT.log>)` `print(<descr>)` `print(<therapyMonitor>)` `print(<therapyMonitor.multi>)` `print(<asymmetricalScatterMatrix>)` `print(<fullFact>)` `print(<confIntOmegaSq>)` `print(<examine>)` `print(<examineBy>)` `print(<frequencies>)` `print(<power.htest.ufs>)` `print(<regrInfluential>)` `print(<nnc>)` `print(<fanova>)` `print(<genlog>)` `print(<ggProportionPlot>)` `print(<logRegr>)` `print(<piecewiseRegr>)`	userfriendlyscience print methods
`processLimeSurveyDropouts()`	processLimeSurveyDropouts
`processLSvarLabels()`	A function to conveniently process LimeSurvey labels
`processOpenSesameIAT()`	processOpenSesameIAT
`pwr.confIntR()`	Determine required sample size for a given confidence interval width for Pearson's r
`pwr.omegasq()`	Power calculations for Omega Squared.
`prob.randomizationSuccess()` `pwr.randomizationSuccess()`	Computations for successful randomization
`regr()`	regr: a simple regression analysis wrapper
`regrInfluential()`	Detecting influential cases in regression analyses
`reliability()`	Reliability function similar to the SPSS RELIABILITY command
`removeExceptionalValues()`	removeExceptionalValues
`rMatrix()`	rMatrix
`rnwString.initiate()` `rnwString.terminate()` `rnwString.generate()` `sanitizeLatexString()` `hasLaTeX()`	rnwString functions
`dRsq()` `pRsq()` `qRsq()` `rRsq()`	The distribution of R squared (as obtained in a regression analysis)
`scaleDiagnosis()`	scaleDiagnosis
`scaleDiagnosisToPDF()`	scaleDiagnosisToPDF
`scaleInspection()` `makeScales()` `meanConfInt()` `sdConfInt()`	scaleInspection and a number of useful helper functions
`scaleStructure()` `scaleReliability()`	scaleStructure
`scatterMatrix()`	scatterMatrix
`scatterPlot()`	Easy ggplot2 scatter plots
`setCaptionNumbering()`	Convenience function for numbered captions in knitr (and so, RMarkdown)
`setFigCapNumbering()` `setTabCapNumbering()`	Automatic caption numbering knitr hooks for figures and tables
`sharedSubString()`	sharedSubString
`showPearsonPower()`	Visualisation of the power of a Pearson correlation test
`simDataSet()`	simDataSet
`Singh`	Verbal and physical aggression scores from Singh et al. (2007)
`sort(<associationMatrix>)`	sort.associationMatrix
`testRetestAlpha()`	testRetestAlpha
`testRetestCES()` `parallelSubscales()`	testRetestCES
`testRetestReliability()`	testRetestReliability
`testRetestSimData`	testRetestSimData is a simulated dataframe used to demonstrate the testRetestAlpha coefficient function.
`therapyMonitor()` `therapyMonitor.multi()`	therapyMonitor & therapyMonitor.multi
`userfriendlyscience-package`	Userfriendlyscience (UFS)
`safeRequire()` `trim()` `noZero()` `formatPvalue()` `formatR()` `repStr()` `repeatStr()` `ifelseObj()` `invertItem()` `is.odd()` `is.even()` `convertToNumeric()` `massConvertToNumeric()` `vecTxt()` `vecTxtQ()` `%IN%`() `cat0()` `addToLog()`	userfriendlyscience basics
`validMeans()` `validSums()`	Only compute means or sums for cases with enough nonmissings

Reference

All functions

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