Observed arrival · 2026-11-07
statforclinicians: a statistical test chooser for clinical studies
A guided tool helps clinicians choose a statistical test based on their study design and outcome, with method guidance and common pitfalls.
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- Clinicians planning or reporting a study
- Worth noticing
- Its examples span outcomes from HbA1c and readmission to censored time-to-event data and agreement between devices.
Field notes
The examples cover a broad clinical-methods range: t-tests and mixed models for continuous outcomes, logistic regression for binary outcomes, and Cox or Fine-Gray methods for time-to-event data. Its pitfalls section gives concrete cautions, including checking a normality plot rather than relying on a normality-test p-value. The page identifies Daniel Wolff, a student of Applied Mathematics at TU Delft, as its maker.
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