The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.