Function reference • ufs

All functions
`A_VarghaDelaney()`	Vargha & Delaney's A
`BAC_plot()`	Bland-Altman Change plot
`CIM()` `CIM_partial()` `knit_print(<CIM>)`	Conceptual Independence Matrix
`%IN%`	Case insensitive version of %in%
`aipedjmv()`	Sample size for accuracy: d
`aiperjmv()`	Sample size for accuracy: r
`areColors()`	Check whether elements of a vector are valid colors
`arr()` `print(<ufsARR>)`	Absolute Relative Risk and confidence interval
`associationMatrix()` `print(<associationMatrix>)` `pander(<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
`attenuate.d()`	Attenuate a Cohen's d estimate for unreliability in the continuous variable
`attenuate.r()`	Attenuate a Pearson's r estimate for unreliability in the measurements
`diamondCoordinates()` `ggDiamondLayer()` `rawDataDiamondLayer()` `varsToDiamondPlotDf()`	Basic ggplot2 diamond plot layer construction functions
`bfi`	25 Personality items representing 5 factors
`biAxisDiamondPlot()`	Diamondplot with two Y axes
`carelessObject()`	Compute diagnostics for careless responding
`carelessReport()`	A report to help diagnosing careless responders
`cat0()`	Concatenate to screen without spaces
`checkDataIntegrity()`	Conveniently checking data integrity
`checkPkgs()`	Check for presence of a package
`cohensdCI()` `dCohensd()` `pCohensd()` `qCohensd()` `rCohensd()` `pdInterval()` `pdExtreme()` `pdMild()` `pwr.cohensdCI()`	The distribution of Cohen's d
`duoComparisonDiamondPlot()` `meansComparisonDiamondPlot()`	meansComparisonDiamondPlot and duoComparisonDiamondPlot
`confIntOmegaSq()` `print(<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
`confIntSD()`	Confidence interval for standard deviation
`confintdjmv()`	Effect Size Confidence Interval: Cohens's d
`confintrjmv()`	Effect Size Confidence Interval: Pearson's r
`convert` `convert.r.to.t` `convert.t.to.r` `convert.b.to.t` `convert.t.to.p` `convert.f.to.p` `convert.f.to.d` `convert.chisq.to.p` `convert.chisq.to.V` `convert.d.to.logodds` `convert.d.to.r` `convert.d.to.t` `convert.d.to.variance` `convert.etasq.to.cohensf` `convert.etasq.to.r` `convert.f.to.etasq` `convert.f.to.omegasq` `convert.fisherz.to.r` `convert.logodds.to.d` `convert.logodds.to.r` `convert.or.to.d` `convert.or.to.r` `convert.r.to.d` `convert.r.to.fisherz` `convert.r.to.p` `convert.t.to.d` `convert.V.to.r` `convert.cohensf.to.omegasq` `convert.cohensfsq.to.omegasq` `convert.means.to.d` `convert.ncf.to.omegasq` `convert.omegasq.to.cohensf` `convert.omegasq.to.cohensfsq` `convert.omegasq.to.f` `convert.percentage.to.se`	conversion functions
`convert.d.to.U3()`	Convert Cohen's d to U3
`convertToNumeric()`	Conveniently convert vectors to numeric
`cramersV()` `print(<CramersV>)` `confIntV()` `print(<confIntV>)`	Cramer's V and its confidence interval
`descr()` `print(<descr>)` `pander(<descr>)` `as.data.frame(<descr>)`	descr (or descriptives)
`diamondPlot()`	Basic diamond plot construction function
`disattenuate.d()`	Disattenuate a Cohen's d estimate for unreliability in the continuous variable
`disattenuate.r()`	Disattentuate a Pearson's r estimate for unreliability
`escapeRegex()`	Escapes any characters that would have special meaning in a reqular expression.
`exceptionalScore()`	Find exceptional scores
`exceptionalScores()`	Find exceptional scores
`exportToHTML()`	Exporting tables to HTML
`extractVarName()`	Extract variable names
`faConfInt()`	Extract confidence bounds from psych's factor analysis object
`fa_failsafe()`	Do factor-analysis, logging warnings and errors
`factorLoadingDiamondCIplot()`	Two-dimensional visualisation of factor analyses
`factorLoadingHeatmap()`	Two-dimensional visualisation of factor analyses
`findShortestInterval()`	Find the shortest interval
`formatCI()`	Pretty formatting of confidence intervals
`formatPvalue()`	Pretty formatting of p values
`formatR()`	Pretty formatting of correlation coefficients
`getData()` `getDat()`	Use a dialog to load data from an SPSS file
`ggBarChart()`	Bar chart using ggplot
`ggBoxplot()`	Box plot using ggplot
`ggEasyBar()` `ggEasyRidge()`	Convenience functions for ggplots based on multiple variables
`ggPie()`	A ggplot pie chart
`ggProportionPlot()` `print(<ggProportionPlot>)` `grid.draw(<ggProportionPlot>)`	Sample distribution based plotting of proportions
`ggSave()`	Save a ggplot with specific defaults
`ggqq()`	Easy ggplot Q-Q plot
`heading()`	Print a heading
`ifelseObj()`	Conditional returning of an object
`insertFigureCaption()` `insertNumberedCaption()` `insertTableCaption()`	Insert numbered caption
`invertItem()` `invertItems()`	invertItems
`iqrOutlier()`	Identify outliers according to the IQR criterion
`irpplot()`	Visualising individual response patterns
`is.nr()`	`NULL` and `NA` 'proof' checking of whether something is a number
`is.odd()` `is.even()`	Checking whether numbers are odd or even
`isTrue()`	More flexible version of isTRUE
`biDimColors()` `uniDimColors()`	Create colours for a response scale for an item
`kblXtra()`	Wrapper for kableExtra for consistent `ufs` table styling
`knitAndSave()`	knitAndSave
`knitFig()`	Easily knit a custom figure fragment
`makeScales()`	Title
`massConvertToNumeric()`	Converting many dataframe columns to numeric
`meanConfInt()` `print(<meanConfInt>)`	A confidence interval for the mean
`meanSDtoDiamondPlot()`	A diamond plot based on means, standard deviations, and sample sizes
`meansDiamondPlot()`	Diamond plots
`meansDiamondPlotjmv()`	Diamond plot: means
`multiResponse()`	Generate a table for multiple response questions
`multiResponsejmv()`	Multi Response
`multiVarFreq()`	Generate a table collapsing frequencies of multiple variables
`convert.cer.to.d()` `convert.d.to.eer()` `convert.d.to.nnc()` `convert.eer.to.d()`	Helper functions for Numbers Needed for Change
`noZero()`	Remove one or more zeroes before the decimal point
`normalHist()` `print(<normalHist>)`	normalHist
`dataShape()` `print(<dataShape>)` `pander(<dataShape>)` `normalityAssessment()` `print(<normalityAssessment>)` `pander(<normalityAssessment>)` `samplingDistribution()`	normalityAssessment and samplingDistribution
`pomegaSq()` `qomegaSq()` `romegaSq()` `domegaSq()`	The distribution of Omega Squared
`opts`	Options for the ufs package
`parallelSubscales()` `print(<parallelSubscales>)`	Split a dataset into two parallel halves
`pwr.bootES()`	Estimate required sample size for accuracy in parameter estimation using bootES
`pwr.confIntProp()`	Estimate required sample size for accuracy in parameter estimation of a proportion
`pwr.confIntR()`	Determine required sample size for a given confidence interval width for Pearson's r
`pwr.omegasq()` `print(<pwr.omegasq>)`	Power calculations for Omega Squared.
`qVec()` `qVecSum()`	Convenience function to quickly copy-paste a vector
`quietRemotesInstall()` `quietGitLabUpdate()`	Quietly update a package from a remote repository
`rbind_df_list()`	Bind lots of dataframes together rowwise
`rbind_dfs()`	Simple alternative for rbind.fill or bind_rows
`regrInfluential()` `print(<regrInfluential>)`	Detecting influential cases in regression analyses
`repeatStr()`	Repeat a string a number of times
`report()`	Output report from results
`safeRequire()`	Load a package, install if not available
`scaleDiagnosis()` `print(<scaleDiagnosis>)` `scaleDiagnosis_partial()` `knit_print(<scaleDiagnosis>)`	scaleDiagnosis
`scaleStructure()` `print(<scaleStructure>)` `scaleStructure_partial()` `knit_print(<scaleStructure>)`	scaleStructure
`scatterMatrix()` `print(<scatterMatrix>)`	scatterMatrix
`setCaptionNumberingKnitrHook()` `setFigCapNumbering()` `setTabCapNumbering()`	Set a knitr hook for caption numbering
`sharedSubString()`	sharedSubString
`simDataSet()`	Simulate a dataset
`spearmanBrown()` `spearmanBrown_reversed()` `spearmanBrown_requiredLength()`	Spearman-Brown formula
`strToFilename()`	Convert a string to a safe filename
`suspectParticipants()`	Selects suspect participants from a `carelessObject`
`testRetestAlpha()` `print(<testRetestAlpha>)`	Test-Retest Alpha Coefficient
`testRetestCES()` `print(<testRetestCES>)`	Test-Retest Coefficient of Equivalence & Stability
`testRetestReliability()` `print(<testRetestReliability>)`	testRetestReliability
`testRetestSimData`	testRetestSimData is a simulated dataframe used to demonstrate the testRetestAlpha coefficient function.
`vecTxt()` `vecTxtQ()` `vecTxtB()` `vecTxtM()`	Easily parse a vector into a character value
`viridisPalette()`	Convenience function to get 2-7 color viridis palettes
`wrapVector()`	Wrap all elements in a vector
`zotero_construct_export_call()`	Construct the URL for a Zotero export call
`zotero_download_and_export_items()`	Download and save all items in a public Zotero group
`zotero_get_all_items()`	Get all items in a public Zotero group
`zotero_nr_of_items()`	Get number of items in a public Zotero group

Reference

All functions