Package: colleyRstats 0.1.1

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_0.1.1.tar.gz
colleyRstats_0.1.1.zip(r-4.7)colleyRstats_0.1.1.zip(r-4.6)colleyRstats_0.1.1.zip(r-4.5)
colleyRstats_0.1.1.tgz(r-4.6-any)colleyRstats_0.1.1.tgz(r-4.5-any)
colleyRstats_0.1.1.tar.gz(r-4.7-any)colleyRstats_0.1.1.tar.gz(r-4.6-any)
colleyRstats_0.1.1.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

On CRAN:

Conda:

5.56 score 2 stars 10 scripts 502 downloads 75 exports 127 dependencies

Last updated from:4a59bce1da. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK281
source / vignettesOK299
linux-release-x86_64OK276
macos-release-arm64OK131
macos-oldrel-arm64OK149
windows-develOK204
windows-releaseOK155
windows-oldrelOK170
wasm-releaseOK227

Exports:%!in%add_pareto_emoa_columnadd_pareto_moocore_columnanalyze_and_reportassumption_methods_textcheck_assumptions_anovacheck_homogeneity_by_groupcheck_normality_by_groupcheckAssumptionsForAnovacite_methodsclassify_outcomecolleyRstats_setupdebug_contr_errordefine_result_macroemit_name_macrosemit_overleafexpand_latex_macrosgenerateEffectPlotgenerateMoboPlotgenerateMoboPlot2ggbetweenstatsWithPriorNormalityCheckggbetweenstatsWithPriorNormalityCheckAsteriskggwithinstatsWithPriorNormalityCheckggwithinstatsWithPriorNormalityCheckAsterisklatex_escapelatex_preamblelatexify_reportn_funna.zeronormalizenot_emptynot_inpathPrepplot_between_statsplot_between_stats_asteriskplot_effectplot_moboplot_mobo2plot_within_statsplot_within_stats_asteriskrecommend_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_datarFromNPAVrFromWilcoxrFromWilcoxAdjustedsave_paper_figurestat_sum_dfuse_colleyrstats_sty

Dependencies:abindafexbackportsBayesFactorbayestestRbitopsbootbroomBWStestcachemcarcarDatacaToolsclicodacolorspaceconfintrcontfraccorrelationcowplotcpp11datawizardDerivdescdeSolvedoBydplyreffectsizeellipticfarverfastmapforcatsforecastFormulafracdiffgenericsggcorrplotggplot2ggpmiscggppggrepelggsideggsignifggstatsplotgluegmpgridExtragtablehypergeoinsightisobandkSampleslabelinglatticelifecyclelme4lmerTestlmtestlubridatemagrittrMASSMatrixMatrixModelsmemoisemgcvminqamodelbasedmodelrmultcompViewmvtnormnlmenloptrnnetnumDerivpaletteerparameterspatchworkpbapplypbkrtestperformancepillarpkgconfigplyrPMCMRpluspolynomprismaticpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRdpackreformulasrematch2reshapereshape2rlangRmpfrrstantoolsrstudioapiS7scalesseeSparseMsplus2RstatsExpressionsstringistringrSuppDistssurvivaltibbletidyrtidyselecttimechangetimeDateurcautf8vctrsviridisLitewithrWRS2xtszoo

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: 2026-07-03
Started: 2026-07-03

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

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: 2026-04-25
Started: 2026-04-25

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
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
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
Configure Global R Environment for colleyRstatscolleyRstats_setup
Replace values across a data framedata the data frame replace_values
Debug contrast errors in ANOVA-like modelsdebug_contr_error
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
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
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
Recommend a principled analysis for one outcomerecommend_analysis recommend_test
Flag suspicious survey responses via the Response Entropy Index (REI)remove_outliers_REI
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. Attention: Effect sizes are not calculated! 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 text. Required commands in LaTeX: '\newcommand{\padjminor}{\textit{p$_{adj}<$}}' '\newcommand{\padj}{\textit{p$_{adj}$=}}' '\newcommand{\rankbiserial}[1]{$r_{rb} = #1$}'reportDunnTest report_dunn_test
report Dunn test as a table. Customizable with sensible defaults. Required commands in LaTeX: '\newcommand{\padjminor}{\textit{p$_{adj}<$}}' '\newcommand{\padj}{\textit{p$_{adj}$=}}' '\newcommand{\rankbiserial}[1]{$r_{rb} = #1$}'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 are provided when possible. 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
Calculation based on Rosenthal's formula (1994). N stands for the _number of measurements_. Necessary command:rFromNPAV
Calculation based on Rosenthal's formula (1994). N stands for the _number of measurements_.rFromWilcox
rFromWilcoxAdjustedrFromWilcoxAdjusted
Save a plot with publication-ready defaultssave_paper_figure
Generating the sum and adding a crossbar.stat_sum_df
Write colleyRstats.sty into a project (for Overleaf)use_colleyrstats_sty