marginaleffects
详尽的工具与示例，帮助将统计模型输出解读为实际边际效应。
marginaleffects 包的手册与方法指南，解释模型到含义的转换。
讲清楚如何把统计模型的输出变成可解释的边际效应、预测值和处理效应（ATE/ATT/CATE）等，适合做回归结果解读、对比、斜率分析或因果推断时用。针对 R 和 Python 的 marginaleffects 包与配套方法，提供 predictions()/comparisons()/slopes() 等函数的使用思路和可视化建议。亮点是把抽象模型结论转成直观、可报告的效应量与置信区间，便于写论文或向非专业读者解释结果。
▸ 展开 SKILL.md 英文原文
Manual for the marginaleffects R and Python package, and guide to the book "Model to Meaning". Use when users ask about predictions, comparisons, slopes, marginal effects, average treatment effects (ATE/ATT/CATE), hypothesis testing, contrasts, counterfactuals, risk ratios, odds ratios, causal inference with G-computation, or need help with marginaleffects functions like predictions(), comparisons(), slopes(), hypotheses(), datagrid(), avg_predictions(), avg_comparisons(), avg_slopes(), or plot functions.
帮我安装这个 skill：https://raw.githubusercontent.com/brycewang-stanford/Auto-Empirical-Research-Skills/main/skills/39-vincentarelbundock-marginaleffects/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/brycewang-stanford/Auto-Empirical-Research-Skills/main/skills/39-vincentarelbundock-marginaleffects/SKILL.md"# marginaleffects Primary source of information: https://marginaleffects.com Free book, case studies, and vignettes are available there. Package manual for R and Python, plus a guide to the companion book. **Book**: *Model to Meaning: How to Interpret Statistical Models in R and Python* - Author: Vincent Arel-Bundock (2026) - Publisher: CRC Press - Free online: https://marginaleffects.com (primary source with many case studies and vignettes) - Print: https://routledge.com/9781032908724 ## Core framework: Five questions for every analysis Every interpretation task can be decomposed into five disciplined questions: 1. **Quantity**: What estimand? (predictions, comparisons, slopes, or tes