jjstatsplot

A wrapper for ggstatsplot: jjstatsplot help researchers to generate plots in jamovi based on ggstatsplot package. Also includes additional plots

Statistical Visualization Made Simple

jjstatsplot brings the power of ggstatsplot to jamovi, making publication-ready statistical visualizations accessible through an intuitive point-and-click interface. This R package bridges the gap between sophisticated statistical plotting and user-friendly data analysis, enabling researchers to create informative plots enriched with statistical details without writing code.

🎯 Why jjstatsplot?

Traditional statistical software often separates visualization from analysis, requiring users to manually annotate plots with statistical results. jjstatsplot integrates these steps, automatically adding appropriate statistical tests, effect sizes, and sample sizes to your visualizations. Whether you're exploring data distributions, comparing groups, examining correlations, or analyzing categorical relationships, jjstatsplot provides the right visualization with the right statistics—all through jamovi's familiar interface.

✨ Key Features

📊 Comprehensive Analysis Types

Category	Analysis	Description	Statistical Details
Continuous	Histogram (jjhistostats)	Distribution visualization	Shapiro-Wilk test, robust measures
Continuous vs Continuous	Scatter Plot (jjscatterstats)	Relationship analysis	Correlation coefficients, regression lines
Continuous vs Continuous	Correlation Matrix (jjcorrmat)	Multiple correlations	Significance levels, correlation strength
Categorical vs Continuous	Box-Violin Plot (jjbetweenstats)	Between-groups comparison	ANOVA, Kruskal-Wallis, post-hoc tests
Categorical vs Continuous	Box-Violin Plot (jjwithinstats)	Within-subjects comparison	Repeated measures ANOVA, Friedman test
Categorical vs Continuous	Dot Chart (jjdotplotstats)	Mean comparisons	Confidence intervals, effect sizes
Categorical vs Categorical	Bar Chart (jjbarstats)	Frequency analysis	Chi-square, Fisher's exact test
Categorical vs Categorical	Pie Chart (jjpiestats)	Proportion visualization	Goodness of fit tests
Distribution	Waffle Chart (jjwaffle)	Part-to-whole visualization	Custom proportions display

🚀 Advanced Capabilities

• Dual-Mode Operation: Analyze single variables or multiple variables simultaneously
• Grouped Analysis: Automatic faceting by grouping variables
• Statistical Flexibility: Choose between parametric, non-parametric, robust, and Bayesian approaches
• Customization Options: Control plot aesthetics, statistical details, and output formatting
• Theme Support: Use jamovi's consistent styling or ggstatsplot's original themes
• Dynamic Sizing: Plots automatically adjust to accommodate your data

📦 Installation

For jamovi Users

1. Open jamovi
2. Go to Modules → jamovi library
3. Search for "jjstatsplot"
4. Click Install

For R Users

# Install from GitHub (latest development version)
if (!require(devtools)) install.packages("devtools")
devtools::install_github("sbalci/jjstatsplot")

# Load the package
library(jjstatsplot)

🏃 Quick Start

In jamovi

1. Open your dataset in jamovi
2. Navigate to the Analyses tab
3. Find jjstatsplot in the analysis menu
4. Select your desired analysis type
5. Drag and drop variables to the appropriate fields
6. Customize options as needed

In R

# Example: Create a histogram with statistical annotations
jjhistostats(
  data = iris,
  dep = "Sepal.Length",
  xlab = "Sepal Length (cm)",
  results.subtitle = TRUE
)

# Example: Compare groups with box-violin plots
jjbetweenstats(
  data = mtcars,
  dep = "mpg",
  group = "cyl",
  type = "nonparametric"
)

🔧 Development

Requirements

• R (≥ 4.0.0)
• jamovi (≥ 1.2.19)
• Core dependencies: jmvcore, R6, ggstatsplot

Building from Source

# Clone the repository
git clone https://github.com/sbalci/jjstatsplot.git

# Install development dependencies
devtools::install_deps()

# Check package
devtools::check()

# Build jamovi module
jmvtools::install()

📚 Documentation

• Package Documentation: sbalci.github.io/jjstatsplot
• ggstatsplot Guide: indrajeetpatil.github.io/ggstatsplot
• jamovi Resources: jamovi.org
• Video Tutorials: YouTube Channel

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

Reporting Issues

• Bug Reports: GitHub Issues
• Feature Requests: GitHub Discussions
• General Questions: [email protected]

📄 Citation

If you use jjstatsplot in your research, please cite:

@software{jjstatsplot,
  author = {Serdar Balci},
  title = {jjstatsplot: Statistical Visualizations for jamovi},
  url = {https://github.com/sbalci/jjstatsplot},
  version = {0.0.3.90},
  year = {2024}
}

Please also cite the underlying packages:

• ggstatsplot: Patil, I. (2021). Visualizations with statistical details: The 'ggstatsplot' approach. Journal of Open Source Software, 6(61), 3167.
• jamovi: The jamovi project (2024). jamovi (Version 2.5) [Computer Software]. Retrieved from https://www.jamovi.org

📝 License

This project is licensed under the GPL (≥ 2) License - see the LICENSE file for details.

🙏 Acknowledgments

• Indrajeet Patil for creating ggstatsplot
• The jamovi team for their excellent statistical platform
• All contributors and users who have helped improve this package

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Made with ❤️ for the jamovi community