Statistical Analysis
/analyze-statsWhat it does
Reproducible Python/R code for 13 analysis types including regression, propensity score, and repeated measures. Calibration mandatory for prediction models.
Highlights
- ✓Regression (logistic/linear), propensity score (PSM/IPTW), repeated measures (GEE/mixed)
- ✓DTA, survival, demographics, agreement
- ✓Publication-ready tables with journal-specific formatting
Install this skill
git clone https://github.com/aperivue/medsci-skills.git
cp -r medsci-skills/skills/analyze-stats ~/.claude/skills/Related skills
Journal-spec figures and visual abstracts: ROC curves, forest plots, flow diagrams, Kaplan-Meier, and more.
Meta-Analysis/meta-analysisFull 8-phase systematic review and meta-analysis pipeline. DTA (bivariate/HSROC) and intervention MA with PRISMA-DTA compliance. Dual-extractor + cohort overlap detection.
Study Replication/replicate-studyReplicate an existing cohort study on a different database. Extracts methodology from a source paper, maps variables via harmonization table, generates analysis code, and produces a replication difference report.
Cross-National Comparison/cross-nationalEnd-to-end cross-national comparison study using parallel survey data. Variable harmonization, parallel weighted analysis (no data pooling), and country-stratified comparison tables.