statdecideR
Automated Statistical Analysis and Plotting with CLD
A lightweight tool that provides a reproducible workflow for selecting and executing appropriate statistical analysis in one-way or two-way experimental designs. The package automatically checks for data normality, conducts parametric (ANOVA) or non-parametric (Kruskal-Wallis) tests, performs post-hoc comparisons with Compact Letter Displays (CLD), and generates publication-ready boxplots, faceted plots, and heatmaps. It is designed for researchers seeking fast, automated statistical summaries and visualization. Based on established statistical methods including Shapiro and Wilk (1965)
statdecideR 
statdecideR is an R package for automatic statistical
decision-making, compact letter displays (CLDs), and beautiful plots
for parametric and non-parametric tests — making your analysis both
robust and publication-ready.
✨ Features
- Automatically detects normality (Shapiro-Wilk test)
- Chooses appropriate test: ANOVA or Kruskal-Wallis
- Performs post-hoc test: Tukey HSD or Multiple Comparisons (agricolae)
- Displays Compact Letter Display (CLD) results
- Generates clean boxplots, heatmaps, and faceted plots
- Fully reproducible and customizable
📦 Installation
# Development version (from local source or GitHub in future)
# install.packages("devtools")
devtools::install_github("yourusername/statdecideR")
⚠ Replace
"yourusername"with your actual GitHub username once hosted.
🛠️ Usage
library(statdecideR)
# Load your data
data <- read.csv("your_data.csv")
# Run analysis and plot
plot_with_cld(
data = data,
dep_var = "pollen", # Your dependent variable
group_var = "month", # Your independent variable (factor)
normal = FALSE # Will be auto-detected in future version
)
📊 Example Output
The package automatically performs: - Statistical test selection - Post-hoc analysis (if significant) - Plot with CLD labels
📄 License
MIT © Subhradip Bhattacharjee