Package: TukeyC 1.4-0

I. B. Allaman

TukeyC: Conventional Tukey Test

Performs multiple comparison analyses using Tukey's Honestly Significant Difference (HSD) test, with intuitive letter grouping of means for balanced and unbalanced designs. Accepts input from 'formula', 'aov', 'lm', 'aovlist', and 'lmerMod' objects, including straightforward handling of interactions. For more details see Tukey (1949) <doi:10.2307/3001913>.

Authors:J. C. Faria [aut], E. G. Jelihovschi [aut], I. B. Allaman [aut, cre]

TukeyC_1.4-0.tar.gz
TukeyC_1.4-0.zip(r-4.7-any)TukeyC_1.4-0.zip(r-4.6-any)TukeyC_1.4-0.zip(r-4.5-any)
TukeyC_1.4-0.tgz(r-4.6-any)TukeyC_1.4-0.tgz(r-4.5-any)
TukeyC_1.4-0.tar.gz(r-4.7-any)TukeyC_1.4-0.tar.gz(r-4.6-any)
TukeyC_1.4-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
TukeyC/json (API)

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

Bug tracker:https://github.com/jcfaria/tukeyc/issues

Datasets:
  • CRD1 - Completely Randomized Design
  • CRD2 - Completely Randomized Design
  • FE - Factorial Experiment
  • LSD - Latin Squares Design
  • RCBD - Randomized Complete Block Design
  • sorghum - Completely Randomized Design
  • SPE - Split-plot Experiment
  • SPET - Split-plot Experiment in Time
  • SSPE - Split-split-plot Experiment

On CRAN:

Conda:

6.97 score 4 stars 84 scripts 601 downloads 7 mentions 8 exports 6 dependencies

Last updated from:c71d102b9c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK123
source / vignettesOK216
linux-releaseOK123
macos-releaseOK122
macos-oldrelOK126
windows-develOK123
windows-releaseOK106
windows-oldrelOK93
wasm-releaseOK99

Exports:boxplot.TukeyCcvplot.TukeyCprint.TukeyCsummary.TukeyCTukeyCxtablextable.TukeyC

Dependencies:emmeansestimabilitymvtnormnumDerivrlangxtable

Introduction to the TukeyC Package
Overview | 1. Quick Start - Completely Randomized Design (CRD) | 2. Accepted Input Classes | 3. Unbalanced Data | 4. Randomized Complete Block Design (RCBD) | 5. Significance Level | 6. Factorial Experiment (FE) | 7. Split-Plot Experiment (SPE) | 8. Visualisation Options | 8.1 Dispersion bars | 8.2 Comparing all four options | 8.3 Boxplot | 9. Tabular Output | 10. Mixed Models with lme4 | References
Rendered fromTukeyC_intro.Rmdusingknitr::rmarkdown

Last update: 2026-05-16
Started: 2026-05-16

Introduction to the TukeyC Package (PDF)
Overview | Quick Start — Completely Randomized Design (CRD) | Accepted Input Classes | Unbalanced Data | Randomized Complete Block Design (RCBD) | Significance Level | Factorial Experiment (FE) | Split-Plot Experiment (SPE) | Visualisation Options | Tabular Output | Mixed Models with lme4 | References
Rendered fromTukeyC_intro_pdf.Rnwusingknitr::knitr

Last update: 2026-05-16
Started: 2026-05-16