ChooseMyStat: A Web-Based Interactive Tool for Statistical Test Selection and Analysis Plan Generation in Clinical Research
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Background
Postgraduate medical residents frequently face difficulty in selecting appropriate statistical tests and preparing statistical analysis plans (SAPs) for thesis work. Existing resources often identify statistical tests without guiding implementation, reporting or software execution.
Aims
To describe the development, features and content validation of ChooseMyStat, a free, open-source, web-based interactive tool for statistical test selection and SAP text generation in clinical research.
Methods
ChooseMyStat was developed as a React-based web application using an iterative, AI-assisted development process under direct faculty supervision. The tool uses a branching decision algorithm covering 18 inferential statistical tests, two diagnostic accuracy measures, four agreement/reliability statistics, and four descriptive statistics scenarios. For each recommendation, it generates a SAP template paragraph, a results reporting example, step-by-step JASP instructions, and R code. Content validation was performed using 105 open-access original research articles from 15 broad medical specialties published in Indian journals during 2024–2025.
Results
The tool covers commonly used statistical methods, including t-tests, ANOVA, chi-square variants, non-parametric alternatives, correlation, regression (linear, logistic, ordinal), survival analysis, methods for clustered or repeated data, diagnostic accuracy measures, and agreement/reliability statistics. Among 365 statistical tests identified across 105 articles (excluding normality-checking procedures), 346 (94.8%) were covered by the tool. Complete coverage of all statistical methods used was observed in 86 of 105 articles (81.9%).
Conclusions
ChooseMyStat integrates statistical test selection with implementation guidance, SAP generation, reporting support and software instructions within a single interface. The tool may support postgraduate research training by improving accessibility to applied biostatistics guidance.
