TukeyC

TukeyC is an R package that implements Tukey’s Honestly Significant Difference (HSD) test as a multiple comparison method in the Analysis of Variance (ANOVA) context, including intuitive letter grouping of means for balanced and unbalanced designs.

Key Features

• Performs the conventional Tukey HSD test with overlapping letter groups for means.
• Accepts input from formula, aov, lm, aovlist, and lmerMod objects.
• Supports single, factorial, split-plot, split-plot in time, and split-split-plot experiments.
• Straightforward handling of interactions via which, fl1, and fl2.
• Adjusted means via Least-Squares Means (emmeans) for unbalanced data.
• Rich plot method with customisable dispersion bands (min–max, SD, CI, pooled CI).
• Reporting support with xtable; additional utilities include boxplot and cv.

Installation

Install from CRAN:

install.packages("TukeyC")

Install the development version from GitHub:

# install.packages("remotes")
remotes::install_github("jcfaria/TukeyC")

Quick Start

library(TukeyC)

## Completely Randomized Design (CRD) — balanced
data(CRD1)

tk1 <- with(CRD1,
            TukeyC(y ~ x,
                   data = dfm,
                   which = 'x'))
summary(tk1)
plot(tk1,
     dispersion = 'sd',
     d.col = 'steelblue')

## Randomized Complete Block Design (RCBD)
data(RCBD)

tk2 <- with(RCBD,
            TukeyC(y ~ blk + tra,
                   data = dfm,
                   which = 'tra'))
summary(tk2)
plot(tk2,
     dispersion = 'ci',
     d.col = 'red')

Project Layout

• /R: Core functions and S3 methods.
• /man: Reference documentation (.Rd files) and dataset documentation.
• /demo: Runnable demos for each experimental design.
• /inst: Package citation file.

Contributing

Contributions are welcome. Open an issue or submit a pull request with:

• Bug fixes and performance improvements.
• Documentation and usability updates.
• New ideas for grouping procedures or graphical displays.

To check and build locally:

R CMD check TukeyC
R CMD build TukeyC
R CMD INSTALL TukeyC_X.X-X.tar.gz

Roadmap

• Expand automated tests (testthat) for all experimental designs.
• Expand vignettes covering balanced and unbalanced use cases.
• Keep documentation aligned with current S3 behaviour.

Developed by:
Faria, J. C.; Jelihovschi, E. G.; Allaman, I. B.
Universidade Estadual de Santa Cruz - UESC
Departamento de Ciencias Exatas - DCEX
Ilheus - Bahia - Brasil