Package: colleyRstats 0.3.1

colleyRstats: Functions to Streamline Statistical Analysis and Reporting

Built upon popular R packages such as 'ggstatsplot' and 'ARTool', this collection offers a wide array of tools for simplifying reproducible analyses, generating high-quality visualizations, and producing 'APA'-compliant outputs. The primary goal of this package is to significantly reduce repetitive coding efforts, allowing you to focus on interpreting results. Whether you're dealing with ANOVA assumptions, reporting effect sizes, or creating publication-ready visualizations, this package makes these tasks easier.

Authors:Mark Colley [aut, cre, cph]

colleyRstats_0.3.1.tar.gz
colleyRstats_0.3.1.zip(r-4.7-any)colleyRstats_0.3.1.zip(r-4.6-any)colleyRstats_0.3.1.zip(r-4.5-any)
colleyRstats_0.3.1.tgz(r-4.6-any)colleyRstats_0.3.1.tgz(r-4.5-any)
colleyRstats_0.3.1.tar.gz(r-4.7-any)colleyRstats_0.3.1.tar.gz(r-4.6-any)
colleyRstats_0.3.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
colleyRstats/json (API)

# Install 'colleyRstats' in R:
install.packages('colleyRstats', repos = c('https://m-colley.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/m-colley/colleyrstats/issues

Pkgdown/docs site:https://m-colley.github.io

On CRAN:

Conda:

6.94 score 4 stars 41 scripts 435 downloads 89 exports 128 dependencies

Last updated from:d83fc4fd22. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK364
source / vignettesOK424
linux-releaseOK379
macos-releaseOK337
macos-oldrelOK368
windows-develOK320
windows-releaseOK359
windows-oldrelOK298
wasm-releaseOK200

Exports:%!in%add_pareto_emoa_columnadd_pareto_moocore_columnanalyze_and_reportanimate_mobo2assumption_methods_textcheck_assumptions_anovacheck_homogeneity_by_groupcheck_normality_by_groupcheck_questionnairecheckAssumptionsForAnovacite_methodsclassify_outcomecolley_themecolleyRstats_setupdebug_contr_errordefine_questionnairedefine_result_macroemit_name_macrosemit_overleafexpand_latex_macrosfigure_base_sizefit_recommendedgenerateEffectPlotgenerateMoboPlotgenerateMoboPlot2ggbetweenstatsWithPriorNormalityCheckggbetweenstatsWithPriorNormalityCheckAsteriskggwithinstatsWithPriorNormalityCheckggwithinstatsWithPriorNormalityCheckAsterisklatex_escapelatex_preamblelatexify_reportlist_questionnairesn_funna.zeronormalizenot_emptynot_inpathPrepplot_between_statsplot_between_stats_asteriskplot_effectplot_fitplot_moboplot_mobo2plot_within_statsplot_within_stats_asteriskquestionnaire_itemsrecommend_analysisrecommend_testremove_outliers_REIreplace_valuesreport_allreport_artreport_art_conreport_art_con_tablereport_clmmreport_dunn_testreport_dunn_test_tablereport_ggstatsplotreport_ggstatsplot_posthocreport_glmmreport_mean_sdreport_nparldreportARTreportArtConreportArtConTablereportCLMMreportDunnTestreportDunnTestTablereportggstatsplotreportggstatsplotPostHocreportGLMMreportMeanAndSDreportNparLDreportNPAVreshape_datareverse_coderFromNPAVrFromWilcoxrFromWilcoxAdjustedsave_paper_figurescore_questionnairescore_reliabilitystat_sum_dfsummarize_sicknessuse_colleyrstats_styuse_study_project

Dependencies:abindafexbackportsBayesFactorbayestestRbitopsbootbroomBWStestcachemcarcarDatacaToolsclicodacolorspaceconfintrcontfraccorrelationcowplotcpp11datawizardDerivdescdeSolvedoBydplyreffectsizeellipticfarverfastmapforcatsforecastFormulafracdiffgenericsggcorrplotggplot2ggpmiscggppggrepelggsideggsignifggstatsplotgluegmpgridExtragtablehypergeoinsightisobandkSampleslabelinglatticelifecyclelme4lmerTestlmtestlubridatemagrittrMASSMatrixMatrixModelsmemoisemgcvminqamodelbasedmodelrmultcompViewmvtnormnlmenloptrnnetnumDerivpaletteerparameterspatchworkpbapplypbkrtestperformancepillarpkgconfigplyrPMCMRpluspolynomprismaticpurrrquantregQuickJSRR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRdpackreformulasrematch2reshapereshape2rlangRmpfrrstantoolsrstudioapiS7scalesseeSparseMsplus2RstatsExpressionsstringistringrSuppDistssurvivaltibbletidyrtidyselecttimechangetimeDateurcautf8vctrsviridisLitewithrWRS2xtszoo

Analyzing a typical user study
The study data | The quick route: one call per dependent variable | Step by step, if you prefer control | 1. Check the assumptions | 2. Plot with automatic test selection | 3. Factorial designs: the Aligned Rank Transform | 4. Descriptives | Into the manuscript | Where to go next
Rendered fromanalyzing-a-user-study.Rmdusingknitr::rmarkdown

Last update: 2026-10-03
Started: 2026-07-16

Choosing the right test (and mixed models)
The idea: scale x dependence x assumptions | recommend_test() as the decision helper | Fitting and reporting the recommended models | Next steps
Rendered fromchoosing-a-test.Rmdusingknitr::rmarkdown

Last update: 2026-10-03
Started: 2026-07-03

Getting started with colleyRstats
Session setup | Example data | Check assumptions | Create a plot | Produce a reporting sentence | Next steps
Rendered fromgetting-started.Rmdusingknitr::rmarkdown

Last update: 2026-10-03
Started: 2026-04-25

Scoring questionnaires
What is available | Scoring | Item columns must be numbers | Declaring the response range | Adding scores to the data | Verify the mapping before you trust the scores | Incomplete responses | Internal consistency | Your own instruments | Sickness over time | Onward
Rendered fromscoring-questionnaires.Rmdusingknitr::rmarkdown

Last update: 2026-10-03
Started: 2026-08-28

From R to Overleaf: publication-ready output
The two macro modes | Tables | Reproducible values | The one-call bundle
Rendered fromoverleaf.Rmdusingknitr::rmarkdown

Last update: 2026-07-03
Started: 2026-07-03

Readme and manuals

Help Manual

Help pageTopics
Add 'PARETO_EMOA' Column to a Data Frameadd_pareto_emoa_column
Add 'PARETO_MOOCORE' Column to a Data Frameadd_pareto_moocore_column
Analyze one dependent variable and produce everything a paper needsanalyze_and_report
Animate a Multi-objective Optimization Plotanimate_mobo2
Methods-section sentence justifying the test selectionassumption_methods_text
Check homogeneity of variances across groupscheck_homogeneity_by_group
Check normality for groupscheck_normality_by_group
Show how a questionnaire will be scored, before scoring itcheck_questionnaire
Check the assumptions for an ANOVA with a variable number of factors: Normality and Homogeneity of variance assumption.checkAssumptionsForAnova check_assumptions_anova
Citations and methods boilerplate for the analyses usedcite_methods
Classify the measurement scale of an outcome variableclassify_outcome
The colleyRstats ggplot2 themecolley_theme
Configure Global R Environment for colleyRstatscolleyRstats_setup
Debug contrast errors in ANOVA-like modelsdebug_contr_error
Register your own questionnairedefine_questionnaire
Define a named LaTeX macro for a single result (single source of truth)define_result_macro
Generate \newcommand stubs for variable/factor namesemit_name_macros
Bundle an analysis into an Overleaf-ready folderemit_overleaf
Expand the colleyRstats LaTeX macros to plain standard LaTeXexpand_latex_macros
Base font size for a figure of a given widthfigure_base_size
Fit the model that the data call for, and report itfit_recommended
Function to define a plot, either showing the main or interaction effect in bold.generateEffectPlot plot_effect
Generate a Multi-objective Optimization PlotgenerateMoboPlot plot_mobo
Generate a Multi-objective Optimization PlotgenerateMoboPlot2 plot_mobo2
Check the data's distribution. If non-normal, take the non-parametric variant of _ggbetweenstats_. x and y have to be in parentheses, e.g., "ConditionID".ggbetweenstatsWithPriorNormalityCheck plot_between_stats
Check the data's distribution. If non-normal, take the non-parametric variant of _ggbetweenstats_. x and y have to be in parentheses, e.g., "ConditionID".ggbetweenstatsWithPriorNormalityCheckAsterisk plot_between_stats_asterisk
Check the data's distribution. If non-normal, take the non-parametric variant of _ggwithinstats_. x and y have to be in parentheses, e.g., "ConditionID".ggwithinstatsWithPriorNormalityCheck plot_within_stats
Check the data's distribution. If non-normal, take the non-parametric variant of _ggwithinstats_. x and y have to be in parentheses, e.g., "ConditionID". Add Asterisks instead of p-values.ggwithinstatsWithPriorNormalityCheckAsterisk plot_within_stats_asterisk
Escape LaTeX special characters in plain textlatex_escape
LaTeX preamble required by the report functionslatex_preamble
Transform text from 'report::report()' into LaTeX-friendly output.latexify_report
List the questionnaires this package can scorelist_questionnaires
Build a median/size label for plot annotationsn_fun
Replace NA values with zerona.zero
This function normalizes the values in a vector to the range [new_min, new_max] based on their original range [old_min, old_max].normalize
Ensure input is not emptynot_empty
Negate '%in%' membership%!in% not_in
Convert Windows paths to R-friendly formatpathPrep
Plot observations with the tests from a fitted analysisplot_fit
The items of one questionnairequestionnaire_items
Recommend a principled analysis for one outcomerecommend_analysis recommend_test
Flag suspicious survey responses via the Response Entropy Index (REI)remove_outliers_REI
Replace values across a data framereplace_values
Analyze and report several dependent variables at oncereport_all
Generate the Latex-text based on the ARTool (see <https://github.com/mjskay/ARTool>). The ART result must be piped into an anova(). Only significant main and interaction effects are reported. P-values are rounded for the third digit. Each effect is accompanied by its partial eta squared, derived from the F statistic and its degrees of freedom with 'effectsize::F_to_eta2()', and a two-sided 95% confidence interval. A term is reported as an interaction when its name contains '":"'; each factor name is rendered as a '\Name' macro only when that is a safe new LaTeX command, and as escaped text otherwise. Attention: the independent variables of the formula and the term specifying the participant must be factors (i.e., use as.factor()).reportART report_art
Report significant ART contrasts (art.con) as LaTeX textreportArtCon report_art_con
Report ART contrasts (art.con) as a LaTeX table. Customizable with sensible defaults. Companion to 'reportDunnTestTable()'.reportArtConTable report_art_con_table
Report a cumulative link (mixed) model in LaTeX/APA stylereportCLMM report_clmm
Report dunnTest as textreportDunnTest report_dunn_test
report Dunn test as a table. Customizable with sensible defaults.reportDunnTestTable report_dunn_test_table
Report statistical details for ggstatsplot.reportggstatsplot report_ggstatsplot
Report significant post-hoc pairwise comparisonsreportggstatsplotPostHoc report_ggstatsplot_posthoc
Report a (generalized) linear mixed model in LaTeX/APA stylereportGLMM report_glmm
Report the mean and standard deviation of a dependent variable for all levels of an independent variable rounded to the 2nd digit.reportMeanAndSD report_mean_sd
Report the model produced by nparLD. The model provided must be the model generated by the command 'nparLD' 'nparLD' (see <https://CRAN.R-project.org/package=nparLD>).reportNparLD report_nparld
Generate the Latex-text based on the NPAV by Lüpsen (see <https://www.uni-koeln.de/~luepsen/R/>). Only significant main and interaction effects are reported. P-values are rounded for the third digit and partial eta squared values, with a two-sided 95% confidence interval, are provided when possible. A term is reported as an interaction when its name contains '":"'. Attention: the independent variables of the formula and the term specifying the participant must be factors (i.e., use as.factor()).reportNPAV
Reshape Excel Data Based on Custom Markers and Include Custom ID Columnreshape_data
Reverse-code responsesreverse_code
Calculation based on Rosenthal's formula (1994). N stands for the _number of measurements_.rFromNPAV
Calculation based on Rosenthal's formula (1994). N stands for the _number of measurements_.rFromWilcox
Effect size r from a multiplicity-inflated Wilcoxon p-value (deprecated)rFromWilcoxAdjusted
Save a plot with publication-ready defaultssave_paper_figure
Score a standardised questionnairescore_questionnaire
Internal consistency of a questionnaire's subscalesscore_reliability
Generating the sum and adding a crossbar.stat_sum_df
Summarise a motion-sickness time coursesummarize_sickness
Write colleyRstats.sty into a project (for Overleaf)use_colleyrstats_sty
Scaffold a reproducible study analysisuse_study_project