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vincentarelbundockvincentarelbundockCommunity·1 Agent Skills Included

marginaleffects

Interpret statistical and machine learning models with predictions, slopes, and contrasts

Computes predictions, comparisons, slopes, and hypothesis tests for over 100 classes of statistical and machine learning models in R and Python. Turns raw model coefficients into clear answers about treatment effects, risk ratios, and marginal effects without manual math. Guides AI agents through a five-question framework to pick the right estimand, grid, aggregation, uncertainty method, and test.
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npx skills add vincentarelbundock/marginaleffects --all -g -y
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Tells the AI agent how the package architecture, testing workflow, and model adapter system are organized so it can correctly write, test, and extend marginaleffects code in Python or R.

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vincentarelbundockvincentarelbundock

marginaleffects

Compute predictions, contrasts, slopes, and hypothesis tests for R and Python models.

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Frequently Asked Questions

FAQPage Schema
How to install marginaleffects?▼

Run `npx skills add vincentarelbundock/marginaleffects --all -g -y` in your terminal to install this skill suite globally for your AI agent.

What does the marginaleffects package do?▼

It computes predictions, contrasts, risk ratios, marginal effects, and hypothesis tests for over 100 types of statistical and machine learning models in R and Python.

How do I compute average treatment effects with AI help?▼

Ask your agent for an ATE or CATE estimate and it will use avg_comparisons() with the right counterfactual grid and standard errors for your model.

Does marginaleffects work with Claude Code and Codex?▼

Yes. The skill follows the universal SKILL.md standard, so agents like Claude Code, Codex, and OpenCode can read the full package manual and book chapters.

Can I use marginaleffects without deep statistics knowledge?▼

Yes. The skill teaches your agent a five-question framework that translates plain-English questions into the correct estimand, function, and code.

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