Durga
Effect Size Estimation and Visualisation
An easy-to-use yet powerful system for plotting grouped data effect sizes.
Various types of effect size can be estimated, then plotted together with a
representation of the original data. Select from many possible data representations
(box plots, violin plots, raw data points etc.), and combine as desired.
'Durga' plots are implemented in base R, so are compatible with base R methods
for combining plots, such as 'layout()'. See Khan & McLean (2023)
Durga: An R package for effect size estimation and visualisation
Effect size estimation and plotting is a component of estimation statistics. Durga is an R package that aims to simplify sophisticated plotting of estimated differences in group means, which is an important part of communicating estimation statistics.
Citation
If you use Durga in your research, please cite (and read) the article:
Khan, M. K., & McLean, D. J. (2024). Durga: An R package for effect size estimation and visualisation. Journal of Evolutionary Biology. doi:10.1093/jeb/voae073
Installation
To install the released version:
> install.packages("Durga")
To install the development version:
> install.packages("devtools") # If not already installed
> devtools::install_github("KhanKawsar/EstimationPlot", build_vignettes = TRUE)
Refer to NEWS.md for a list of changes in each version, including changes in the current development version. You can read the news for an installed package by running:
> news(package = "Durga")
Usage
Read the paper Khan & McLean (2023) for a detailed description of the package. Once Durga is installed, you can read the vignette named Introduction to Durga for a shorter introduction to using Durga, complete with examples and code.
# Display the vignette in a browser
RShowDoc("Durga-intro", package = "Durga")
# Display the vignette in the help window pane
vignette("Durga-intro", package = "Durga")
A minimal example using constructed data:
n <- 100
df <- data.frame(val = c(rnorm(n), rnorm(n, mean = 1)),
group = c(rep("Control", n), rep("Group", n)))
d <- DurgaDiff(df, data.col = "val", group.col = "group")
# or equivalently
d <- DurgaDiff(val ~ group, df)
DurgaPlot(d)
Development Environment
─ Packages ─────────────────────────────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
cachem 1.1.0 2024-05-16 [1] CRAN (R 4.4.2)
cli 3.6.3 2024-06-21 [1] CRAN (R 4.4.2)
devtools 2.4.5 2022-10-11 [1] CRAN (R 4.4.2)
digest 0.6.37 2024-08-19 [1] CRAN (R 4.4.2)
ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.4.2)
evaluate 1.0.3 2025-01-10 [1] CRAN (R 4.4.2)
fastmap 1.2.0 2024-05-15 [1] CRAN (R 4.4.2)
fs 1.6.5 2024-10-30 [1] CRAN (R 4.4.2)
glue 1.8.0 2024-09-30 [1] CRAN (R 4.4.2)
htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.4.2)
htmlwidgets 1.6.4 2023-12-06 [1] CRAN (R 4.4.2)
httpuv 1.6.15 2024-03-26 [1] CRAN (R 4.4.2)
knitr 1.49 2024-11-08 [1] CRAN (R 4.4.2)
later 1.4.1 2024-11-27 [1] CRAN (R 4.4.2)
lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.4.2)
magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.4.2)
memoise 2.0.1 2021-11-26 [1] CRAN (R 4.4.2)
mime 0.12 2021-09-28 [1] CRAN (R 4.4.0)
miniUI 0.1.1.1 2018-05-18 [1] CRAN (R 4.4.2)
pkgbuild 1.4.5 2024-10-28 [1] CRAN (R 4.4.2)
pkgload 1.4.0 2024-06-28 [1] CRAN (R 4.4.2)
profvis 0.4.0 2024-09-20 [1] CRAN (R 4.4.2)
promises 1.3.2 2024-11-28 [1] CRAN (R 4.4.2)
purrr 1.0.2 2023-08-10 [1] CRAN (R 4.4.2)
R6 2.5.1 2021-08-19 [1] CRAN (R 4.4.2)
Rcpp 1.0.13-1 2024-11-02 [1] CRAN (R 4.4.2)
remotes 2.5.0 2024-03-17 [1] CRAN (R 4.4.2)
rlang 1.1.4 2024-06-04 [1] CRAN (R 4.4.2)
rmarkdown 2.29 2024-11-04 [1] CRAN (R 4.4.2)
rstudioapi 0.17.1 2024-10-22 [1] CRAN (R 4.4.2)
sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.4.2)
shiny 1.10.0 2024-12-14 [1] CRAN (R 4.4.2)
urlchecker 1.0.1 2021-11-30 [1] CRAN (R 4.4.2)
usethis 3.1.0 2024-11-26 [1] CRAN (R 4.4.2)
vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.4.2)
xfun 0.50 2025-01-07 [1] CRAN (R 4.4.2)
xtable 1.8-4 2019-04-21 [1] CRAN (R 4.4.2)
yaml 2.3.10 2024-07-26 [1] CRAN (R 4.4.2)