Our Mission
CrossTabs exists to make rigorous statistical analysis of categorical data accessible to everyone — researchers, students, clinicians, and analysts — without requiring expensive software licenses or advanced programming skills. We believe that the tools used to analyze data should be free, transparent, and respect user privacy.
What CrossTabs Does
CrossTabs provides a suite of free, browser-based tools for categorical data analysis and contingency table methods. Our calculator handles the full workflow from data input through interpretation:
- Chi-square tests for independence, goodness of fit, and homogeneity
- Fisher's exact test for small-sample and sparse-table analysis
- Effect size measures including Cramér's V (with bias correction), phi coefficient, odds ratios, and relative risk
- Post-hoc analysis with adjusted standardized residuals
- Power analysis for sample size planning
- Cohen's kappa for inter-rater agreement
- APA-formatted output ready for publication
Methodology
Every statistical method in CrossTabs is implemented following peer-reviewed literature and established standards. We do not invent novel procedures; instead, we faithfully implement well-validated methods so researchers can trust the output.
Foundational References
- Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. — Effect size benchmarks and power analysis methods.
- Agresti, A. (2013). Categorical Data Analysis (3rd ed.). Wiley. — Core contingency table methods, Fisher's exact test, and log-linear models.
- American Psychological Association. (2020). Publication Manual of the American Psychological Association (7th ed.). — APA-formatted reporting of statistical results.
- Bergsma, W. (2013). A bias-correction for Cramér's V and Tschuprow's T. Journal of the Korean Statistical Society, 42(3), 323–328. — Bias-corrected effect size estimation.
- Fisher, R. A. (1922). On the interpretation of chi-square from contingency tables. Journal of the Royal Statistical Society, 85(1), 87–94. — Fisher's exact test foundations.
Core calculations run locally in your browser, and our source code is publicly available for inspection. Researchers can compare implementations against published formulas and review the public Validation Kit for benchmark cases and release targets.
Privacy Commitment
CrossTabs was designed with privacy and trust as first-class product constraints:
- Browser-first analysis — the main calculator workflow runs locally instead of requiring raw-dataset upload for core statistics.
- Transparent storage — browser storage is used for session recovery, saved work, and preferences.
- Documented integrations — optional telemetry, hosting infrastructure, and opt-in AI features are described in the privacy policy.
- Public validation — benchmark matrices and release regression targets are published so users can inspect the current validation scope.
- Sensitive-data caution — many teams use CrossTabs for sensitive workflows, but it is not represented as a HIPAA-compliant service and organizations should review their own obligations.
Read the full Privacy Policy and Validation Kit for the current trust posture.
Open Source
CrossTabs is open-source software. The full source code is available on GitHub:
View on GitHub →
We welcome contributions, bug reports, and feature requests. Whether you are a statistician who wants to verify a formula, a developer who wants to improve the interface, or a researcher who needs a new test added, the project is open to collaboration.
Contact & Contribute
The best ways to reach us or contribute to the project:
Try CrossTabs
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