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docs(community): add SUPPORT.md and GitHub issue templates
JOSS reviewer checklist requires clear pathways for: (1) contributing, (2) reporting issues, (3) seeking support. CONTRIBUTING.md and CODE_OF_CONDUCT.md already covered (1) and conduct; this commit fills in the issue-reporting and support pathways. Added: - SUPPORT.md: where to ask usage questions (Discussions), where to file bugs (Issues + bug_report template), how to report security issues privately (email), and response-time expectations. - .github/ISSUE_TEMPLATE/bug_report.md: structured form including version probe, minimal-reproducible-example block keyed to bundled sp.datasets, and a dedicated section for numerical-correctness reports against Stata / R / source-paper reference implementations. - .github/ISSUE_TEMPLATE/feature_request.md: structured form including proposed API sketch and a required References section (DOI / arXiv ID for new estimators, since this project's correctness policy forbids unverified citations). - .github/ISSUE_TEMPLATE/config.yml: disable blank issues; route how-do-I questions to Discussions and security reports to private email instead of the public tracker. Pre-review smoke test confirmed the README Quick Start exercises (DiD callaway_santanna on mpdta, IV ivreg on card_1995, RD rdrobust on lee_2008_senate, Synth on california_prop99) all run end-to-end in a fresh venv via `pip install statspai` and return numbers matching the README's stated expectations.
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---
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name: Bug report
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about: Report a crash, incorrect number, documentation error, or behavior that contradicts the docstring/paper
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title: "[bug] <short description>"
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labels: bug
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assignees: ''
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---
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## Summary
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<!-- One sentence: what is wrong. -->
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## Environment
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- StatsPAI version: <!-- python -c "import statspai as sp; print(sp.__version__)" -->
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- Python version: <!-- python --version -->
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- OS: <!-- macOS / Linux / Windows + version -->
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- Install source: <!-- pip install statspai / pip install -e . / conda / source build -->
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- Extras installed (if any): <!-- e.g. [plotting], [fixest], [neural], [performance], [bayes] -->
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## Minimal reproducible example
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<!--
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If at all possible, please use one of the bundled teaching datasets under
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`sp.datasets` (mpdta, card_1995, lee_2008_senate, california_prop99, ...)
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so we can run the example directly.
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-->
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```python
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import statspai as sp
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# your minimal example here
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```
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## What you expected
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<!-- The number / behavior you expected. Reference the docstring, paper,
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or reference implementation (Stata / R / other) if applicable. -->
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## What actually happened
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<!-- Paste the error traceback or the unexpected output. -->
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```
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<traceback or output here>
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```
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## Numerical-correctness notes (if applicable)
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<!-- For estimator-level numerical issues, fill in:
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- Reference implementation tried for comparison (Stata package / R package / source paper)
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- Version of that reference (Stata 18, fixest 0.11, did 2.1.2, etc.)
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- The number it returns vs. what StatsPAI returns
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- A reproducible script if possible
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-->
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## Anything else
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<!-- Logs, screenshots, related issues, suspected cause. -->

.github/ISSUE_TEMPLATE/config.yml

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blank_issues_enabled: false
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contact_links:
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- name: Usage question / how-do-I
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url: https://github.com/brycewang-stanford/StatsPAI/discussions
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about: For "how do I do X", methodological discussion, or comparing results across Stata/R/StatsPAI — please use GitHub Discussions.
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- name: Security vulnerability
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url: mailto:brycew6m@stanford.edu
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about: Please report security issues privately via email, not as a public issue.
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---
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name: Feature request / new estimator
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about: Suggest a new feature, estimator, or improvement
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title: "[feature] <short description>"
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labels: enhancement
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assignees: ''
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---
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## What you would like
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<!-- One paragraph: the feature, estimator, or improvement you're proposing. -->
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## Motivation
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<!-- Why is this useful? What problem does it solve? Who benefits? -->
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## Proposed API (if applicable)
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<!-- A sketch of what calling this would look like. Match StatsPAI's existing
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`sp.<verb>(data=..., ...)` style where possible. -->
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```python
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import statspai as sp
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# proposed usage
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```
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## References
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<!-- For new estimators, this section is required:
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- Source paper(s) with DOI or arXiv ID
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- Existing reference implementations (Stata package, R package, etc.)
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- Any benchmarks or canonical datasets the estimator is usually tested on
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-->
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## Alternatives considered
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<!-- What other approaches did you consider? Are there existing functions in
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StatsPAI (or Stata / R) that partially address this? -->
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## Anything else
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<!-- Notes on numerical pitfalls, edge cases, scope, or anything else
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that would help us scope the work. -->

SUPPORT.md

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# Getting Support for StatsPAI
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Thanks for using StatsPAI. Pick the channel that fits what you need.
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## Asking a question or discussing usage
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For "**how do I**", "**which estimator should I use**", "**why does my result differ from Stata / R**", or general usage discussion:
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- **GitHub Discussions**<https://github.com/brycewang-stanford/StatsPAI/discussions>
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- Best place for open-ended questions, methodological discussion, and Q&A that may help future users.
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- Please search existing threads first — many common questions are already answered.
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When asking, please include:
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1. StatsPAI version: `python -c "import statspai as sp; print(sp.__version__)"`
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2. Python version + OS
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3. Minimal reproducible example (data + code, ideally using one of the bundled `sp.datasets`)
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4. What you expected vs. what you got
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## Reporting a bug
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If something is **wrong** — a crash, an incorrect number, a documentation error, or behavior that contradicts the docstring / paper:
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- **GitHub Issues**<https://github.com/brycewang-stanford/StatsPAI/issues>
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- Use the **Bug report** template.
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- Numerical-correctness issues (estimator returns a different value than Stata / R / the source paper) are top priority. Please cite the reference implementation and version when relevant.
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## Requesting a feature or new estimator
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- **GitHub Issues** — use the **Feature request / new estimator** template.
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- For new estimators, please link to the source paper (with DOI) and, if possible, a reference implementation in Stata, R, or another package.
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## Security issues
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If you believe you have found a security vulnerability (e.g., a code path that allows arbitrary code execution from data input), please **do not** open a public issue. Email the maintainer directly:
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- **Email:** brycew6m@stanford.edu
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## Commercial support and collaboration
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StatsPAI is developed by the team behind [CoPaper.AI](https://copaper.ai) (Stanford REAP). For applied-econometrics consulting, custom-estimator collaborations, or institutional licensing questions, email brycew6m@stanford.edu.
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## Response time expectations
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StatsPAI is maintained primarily by a small team. We aim to triage issues within 1–2 weeks. For urgent numerical-correctness bugs or breakage in core estimators (`did`, `iv`, `rd`, `synth`, `dml`, `panel`), we will respond faster.

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