A comprehensive jamovi module for chi-squared analysis of contingency tables, designed as an educational resource for undergraduate students learning categorical data analysis.

ChiSquaredTools provides a point-and-click interface for contingency table analysis, addressing the challenge students face when learning both statistical concepts and software simultaneously. The module includes extensive pedagogical scaffolding with toggleable method explanations, academic citations, and interpretation guidance.

The module includes six analytical facilities accessible from the Chi² Tools menu in jamovi:

Chi-squared test of independence with multiple testing methods:

• Traditional Pearson chi-squared test
• (N−1)/N adjusted chi-squared test (for small samples)
• Permutation-based exact test
• Monte Carlo test with Phipson & Smyth (2010) p-value computation
• M test (maximum adjusted residual method)

Over 20 association measures organised by statistical foundation:

• Chi-squared-based measures (Cramér's V, Contingency Coefficient, etc.)
• Margin-free measures (Yule's Q, Odds Ratio, etc.)
• Proportional Reduction in Error (PRE) measures (Lambda, Tau, Uncertainty Coefficient, etc.)
• Bootstrap confidence intervals for selected measures

Cell-level diagnostic metrics including:

• Standardised and adjusted standardised residuals
• Moment-corrected standardised residuals
• Quetelet Index and IJ association factor
• Backwards-stepping outlier detection
• PEM (Percentage of Maximum Deviation) with bootstrap confidence intervals
• Median polish residuals (standardised and adjusted)
• Goodman-Kruskal residuals
• Difference in Estimated Proportions (DEP)

Hierarchical clustering analysis using:

• Ward's method with chi-squared distance (Greenacre, 2017)
• Significance testing
• Dendrogram visualisation

For 2×2 tables across K strata:

• Cochran-Mantel-Haenszel test for conditional independence
• Mantel-Haenszel pooled odds ratio with confidence intervals
• Breslow-Day and Tarone tests for homogeneity of odds ratios
• Stratum-specific statistics and forest plots

For general R×C tables across K strata:

• Generalised Cochran-Mantel-Haenszel test
• Log-linear homogeneity test
• Stratum-specific chi-squared statistics

Each facility includes:

• Method explanations: Toggleable descriptions with rationale, formulas, and usage guidance
• Automatic highlighting: Significant or noteworthy results are colour-coded for easy identification
• Academic citations: Proper references to statistical literature throughout
• Interpretation guidance: Decision support for choosing appropriate methods

(Coming soon — pending submission to the jamovi module store)

Once available, this will be the recommended installation method, as the jamovi library provides pre-built versions for all supported platforms (Windows, macOS Intel, macOS Apple Silicon, and Linux).

Option 1: Pre-built module

1. Download the .jmo file from the Releases page
2. In jamovi, go to Modules → jamovi library → Sideload (⋮ menu)
3. Select the downloaded .jmo file

⚠️ Important: The pre-built .jmo file was compiled on macOS (Apple Silicon) with jamovi 2.6.x. It will work on Macs running jamovi 2.6.x (Apple Silicon version). It may not work on:

• Windows or Linux systems
• Macs running the Intel version of jamovi
• Systems running jamovi 2.7.x or later

Users in these situations should use Option 2 below.

Option 2: Build from source (all platforms)

If the pre-built .jmo file is not compatible with your system, you can build the module from source:

1. Ensure you have R and the jmvtools package installed:

   install.packages('jmvtools', repos = c('https://repo.jamovi.org', 'https://cran.r-project.org'))

2. Clone or download this repository
3. Open R in the repository directory and run:

   jmvtools::install()

This will compile the module for your specific platform and install it into your local jamovi installation.

• jamovi 2.6 or later
• R 4.4.1 or later (bundled with jamovi; required only if building from source)

Gianmarco Alberti
University of Malta
Email: gianmarco.alberti@um.edu.mt

If you use this module in your research or teaching, please cite:

Alberti, G. (2025). ChiSquaredTools: Chi-Squared Analysis Tools [jamovi module]. Version 1.0.0. https://github.com/gianmarcoalberti/ChiSquaredTools

• chisquare: The author's CRAN package providing many of the underlying statistical functions
• stratastats: The author's CRAN package providing many of the underlying statistical functions
• From Data to Insights: A Beginner's Guide to Cross-Tabulation Analysis (Chapman & Hall, 2024. ISBN 9781032720388)

This project is licensed under the GNU General Public License v3.0 — see the LICENSE file for details.