brycewang-stanford/Auto-Empirical-Research-Skills✦ 精选0°

StatsPAI_skill

仓库创建 2026年4月3日最近提交 20 天前SkillHot 收录 20 天前

⬈ GitHub 仓库 ⬈ SKILL.md 原文件 ⬇ Raw 原始文件

▸ 精选理由

适合需要自动化、可复现经济实证分析的研究者与流水线。

▸ 风险提示

需安装大量第三方包并在可执行环境中运行代码。

这个 Skill 做什么

一站式 Python 因果推断与计量经济学工具包，含大量估计器与导出功能。

一套在 Python 里做完整实证/因果分析的工具链，默认输出 AER 风格的论文结果（DID、RD、IV、SCM、DML 等）。适合要跑一整套分析流程、生成 Table/Figure、写出估计方程和假设、做稳健性检验并导出 LaTeX/Word/Excel 时使用。特色是集成大量估计器和报告导出能力，也支持流行的流行病学与 ML 因果方法，方便把分析结果直接变成交付物。

▸ 展开 SKILL.md 英文原文

Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 / Table 2 / event-study figure / robustness gauntlet — OR in epidemiology / public health style (target-trial emulation, IPTW + g-formula + TMLE triplet, Mendelian randomization, KM/AFT survival, E-value sensitivity, STROBE/TRIPOD reporting) — OR in ML causal inference style (DML, S/T/X/R/DR meta-learners, causal forest, Dragonnet/TARNet/CEVAE, BCF, CATE distribution, policy learning, conformal causal, fairness audit, causal discovery). Also covers exporting multi-column regression tables to Word / Excel / LaTeX (Stata outreg2 / esttab / R modelsummary equivalent) and bundling an entire replication appendix into one .docx / .xlsx / .tex file. Triggers on keywords "StatsPAI", "statspai", "AER empirical analysis", "appl

研究检索因果推断计量经济学Python通用

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帮我安装这个 skill：https://raw.githubusercontent.com/brycewang-stanford/Auto-Empirical-Research-Skills/main/skills/00-Full-empirical-analysis-skill_StatsPAI/SKILL.md

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SKILL.MD 节选查看完整文件 ↗

# StatsPAI: Agent-Native Causal Inference & AER-Style Empirical Workflow

StatsPAI is a validation-tiered Python package for causal inference and applied econometrics: one `import statspai as sp`, 1,100+ registered functions behind a self-describing API, and mature estimator result objects that commonly export to LaTeX / Word / Excel / BibTeX.

This skill drives StatsPAI through the **canonical pipeline of an applied AER empirical paper**. Each step emits a paper-ready artifact (Table 1, event-study figure, Table 2 main results, robustness panel, replication stamp).

- **Source**: https://github.com/brycewang-stanford/StatsPAI
- **Install**: `pip install "statspai[fixest,plotting]"` (API sur

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