Package index • SciDataReportR

All functions

AddToCodebook(): Add a new variable to a codebook
ApplyNormativeTScores(): Apply a normative T-score model to new data
AssemblePlots(): Assemble ggplot objects into a unified multi-panel figure
CalcMScore(): Calculate robust M-scores for numeric variables
CalcZScore(): Calculate Z-scores (or standardized scores) and return data + parameters
CodebookMergeApp(): Interactive codebook harmonization dashboard
CombineCodebooks(): Combine Two Codebooks with Conflict Detection
ConvertOrdinalToNumeric(): ConvertOrdinalToNumeric
CreateMCAObject(): Create a reusable MCA object and visualizations
CreateMCATable(): Create MCA table and visualization
CreateMScoreObject(): Calculate robust M-scores for numeric variables
CreateNormativeTScoreModel(): Create normative T-scores from a regression model
CreateNormativeTScores(): Create normative T-scores from a regression model
CreatePCAObject(): Create a reusable PCA object and visualizations
CreatePCATable(): Create PCA table and visualization
CreatePathwayPlot_KT(): Create Kynurenine-Tryptophan Pathway Plot
CreateProjectFolders(): Create Project Folder Structure
CreateRCIObject(): Create a Reliable Change Index (RCI) object
CreateSOMClusterModel(): SOM + latent profile clustering pipeline (with AHP and distance baselines)
CreateStatisticsTable(): Create Statistics Table
CreateSummaryTable(): Create Summary Table
CreateVariableTypesTemplate(): Create a Template for Variable Types
CreateZScoreObject(): Calculate Z-scores (or standardized scores) and return data + parameters
CreateZScorePlot(): Create a Z-score plot with statistical significance
ExtractPCAComponentSummary(): Extract PCA component summaries
FormattedDataDictionary(): Create a formatted data dictionary table
IQROutliers(): Detect outliers using the Tukey IQR rule and visualize results
InsertValues(): Insert Values into a String Array
InspectCategoricalSummary(): Inspect categorical variables
KeepEnv(): Keep selected objects in an environment and remove everything else
MakeComparisonTable(): Make comparison table with covariate adjustment, effect sizes, and pairwise contrasts
MakeDataDictionary(): Create a data dictionary for a data frame
MakeFacetCatComparisonTable(): Create a merged gtsummary table by faceting comparisons across multiple categorical variables
MakeTable1(): Create Summary Table using gtsummary
Make_DataDictionary(): Create a data dictionary for a data frame
MergeCodebooks(): Merge multiple codebooks using harmonization rules
Merge_ByClosestTime(): Merge Two Data Frames by Closest Time
Pipeline_SOMClust(): SOM + latent profile clustering pipeline (with AHP and distance baselines)
Plot2GroupStats(): Plot & Summarize Group Stats via MakeComparisonTable (BH q from p; SHAPE by p; COLOR by Category (vector or data frame); stable point size; palette via paletteer)
PlotAnovaRelationshipsMatrix(): Plot ANOVA Relationships Matrix
PlotAssociations(): Plot Associations
PlotBlandAltman(): Plot Bland-Altman Agreement Plot
PlotCatInteractionEffectsMatrix(): Plot Categorical Interaction Effects Matrix
PlotCategoricalDistributions(): Plot categorical distributions
PlotChiSqCovar(): Plot Chi-Square Tests for Categorical Associations (optionally stratified by covariates)
PlotContinuousDistributions(): Plot Continuous Distributions
PlotCorrelationsHeatmap(): Plot correlations heatmap
PlotDirectionalHeatmaps(): Create directional heatmaps across continuous & binary variables
PlotInteractionEffectsContinuous(): Plot Single Interaction Effect
PlotInteractionEffectsMatrix(): Plot Interaction Effects Matrix
PlotMiningMatrix(): PlotMiningMatrix
PlotMissingData(): Plot Missing Data
PlotNumInteractionEffectsMatrix(): Plot Numerical Interaction Effects Matrix
PlotPValueComparisons(): Plot P-Value Comparisons
PlotPartialRegressionScatter(): Partial Regression Plot
PlotPathway_KT(): Plot the kynurenine-tryptophan pathway
PlotPhiHeatmap(): Plot Phi Correlations Between Binary Variables
PlotPointCorrelationsHeatmap(): Plot Point-Biserial Correlations Between Binary and Continuous Variables
PlotSpiderChart(): Plot a spider chart across continuous and binary variables
PlotSplitViolin(): Split violin with aligned half-boxplots, significance label, sample sizes, and label-aware title
PlotSwimmerTransitions(): Plot swimmer-style transitions for a binary condition over repeated visits
PlotTimeDistribution(): Plot Time Distribution
PlotZScore(): Plot Z-score group differences with statistical significance
PrepNumericData(): Prepare numeric data safely for analysis
ProjectPCA(): Project PCA scores onto new data
ProjectRCI(): Project a trained RCI object onto new data
ProjectSOMCluster(): Project new data onto an existing SOM + cluster solution
ProjectZScore(): Project standardized scores onto new data using external parameters
Project_SOMClust(): Project new data onto an existing SOM + cluster solution
Project_ZScore(): Project standardized scores onto new data using external parameters
ReValueFactors(): Revalue Factors
ReplaceMissingCode(): Replace Missing Codes with NA
ReplaceMissingLabels(): Replace Missing Labels in Dataframe Columns
RevalueData(): Revalue Data
SampleData: SampleData for practicing SciDataReportR functions
SampleVariableTypes: Example Dataset: SampleVariableTypes
SummarizeTransitions(): Summarize participant transitions for a binary longitudinal condition
UnivariateRegressionTable(): Univariate Regression Table
UpdateCodebook(): Update an existing codebook based on a given dataframe
UpdateDataDictionary(): Update an existing data dictionary with new variables and types
add_r_and_stars(): Add r-values and significance stars to a correlations heatmap
calculate_pathway_results(): Calculate Pathway Results for Metabolite Comparisons
createBinaryMapping(): Create a Mapping Table for Binary Variables
createFacetLabels(): Create facet labels for ggplot2 based on variable labels in a data frame
geom_starcaption(): Add a Caption Explaining Star Annotations
getBinaryVars(): Identify Binary Variables
getCatVars(): Get Categorical Variables
getNumVars(): Get Numeric Variables
`%!in%`: Negated "in" Operator
plotForestFromTable(): Create a Forest Plot from Univariate Regression Tables
plotPCA(): Plot 3D PCA Scores
plotSigAssociations(): Plot Significant Associations
plotSigCorrelations(): Plot Significant Correlations
removeString(): Remove Strings from a Vector
reverseFactorLevels(): Reverse Levels of Categorical Factors
use_EDATemplate(): Use the EDATemplate Quarto Template
windsorize(): Winsorize a numeric vector using SD or IQR thresholds