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boxTest

The boxTest package provides a simple way to compare two groups using boxplots and statistical tests. It automatically checks normality (via Shapiro–Wilk test) and then applies the appropriate test:

• Independent 2-sample t-test (if both groups are normally distributed)
• Mann–Whitney U test (if at least one group is non-normal)

It also generates a publication-ready boxplot with jittered points.

Installation

From GitHub (development version)

# install.packages("remotes")  # if not already installed
remotes::install_github("arka1985/boxTest")

From CRAN (once accepted)

install.packages("boxTest")

From tar.gz release

Download the .tar.gz file from Releases and install locally:

install.packages("path/to/boxTest_0.1.0.tar.gz", repos = NULL, type = "source")

Example

library(boxTest)

# Create a sample dataset: Male and Female BMI
df <- data.frame(
  gender = rep(c("Male", "Female"), each = 10),
  BMI = c(22, 24, 25, 23, 26, 28, 24, 23, 27, 25,
          21, 22, 23, 20, 24, 22, 21, 23, 22, 21)
)

# Compare BMI between Male and Female
res <- compare_two_groups(df, "BMI", "gender")

# Show the boxplot
print(res$plot)

# Normality test results
print(res$normality)

# Test summary (t-test or Mann–Whitney U)
print(res$test_summary)

Output

• res$plot → A ggplot object showing the boxplot with jittered points
• res$normality → Shapiro–Wilk test results for each group
• res$test_summary → Test used, statistic, df (if applicable), and p-value

Authors

• Arkaprabha Sau (Author & Maintainer)
• Santanu Phadikar (Author)
• Ishita Bhakta (Author)

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.