AssociationExplorer: A user-friendly Shiny application for exploring associations and visual patterns
AssociationExplorer is a user-friendly, open-source R Shiny application that helps non-technical users explore statistical associations within multivariate datasets. It is especially designed for journalists, educators, and engaged citizens interested in uncovering meaningful patterns in survey or public data without requiring advanced programming or statistical expertise.
- Interactive upload of CSV or Excel datasets
- Optional upload of a variable description file
- Automatic handling of quantitative and qualitative variables
- Computation of association measures: Pearson's r, Eta, and Cramer's V
- Dynamic filtering of associations by user-defined thresholds
- Interactive correlation network visualization
- Contextual bivariate plots: scatter plots, mean plots, and contingency tables
- One-click export of visualizations and tables as PNG images
- Clean, modern UI with responsive behavior
You can launch the app directly from R using:
library(shiny)
runGitHub("AssociationExplorer", "AntoineSoetewey")You will need the shiny package installed (install.packages("shiny")) and an active internet connection.
Full documentation, including how to use the app, variable formats, data requirements, and example workflows, is available in the documentation folder of this repository.
An accompanying paper can be found in the paper folder, which provides a detailed overview of the application, its features, and its intended use cases.
The repository includes an illustrative example based on the European Social Survey, restricted to Belgian respondents and curated for demonstration purposes. The code used to generate the curated dataset can be found in the data folder.
If you use the dataset used in the example, please cite the following:
- European Social Survey European Research Infrastructure (ESS ERIC). (2024). ESS11 integrated file, edition 3.0 [Data set]. Sikt - Norwegian Agency for Shared Services in Education and Research. https://doi.org/10.21338/ess11e03_0
This project is licensed under the MIT License.
For questions, suggestions, or contributions, feel free to open an issue on the GitHub repository.