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tooluniverse-statistical-modeling

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Statistical modeling and regression analysis for biomedical data. Linear/logistic/ordinal regression, Cox proportional hazards, mixed-effects models, ANOVA, with odds ratios, hazard ratios, confidence intervals, and model diagnostics.

scientific-skills/Data Analysis/tooluniverse-statistical-modeling/SKILL.md

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> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)


# Statistical Modeling for Biomedical Data Analysis

Comprehensive statistical modeling skill for fitting regression models, survival models, and mixed-effects models to biomedical data. Produces publication-quality statistical summaries with odds ratios, hazard ratios, confidence intervals, and p-values.

## When NOT to Use

- Do not use for machine learning prediction tasks (classification accuracy, AUC) — use scikit-learn instead.
- Do not use for deep learning or neural network models — use PyTorch or TensorFlow.
- Do not use for causal inference (DAGs, counterfactuals) — use DoWhy or CausalML.
- Do not use when data has not been inspected for missing values, collinearity, or separation — always run Phase 0 first.

## Features
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