Agent skill · Testing & QA

analyze

Confirmatory hypothesis testing matched to pre-registration, with full assumption testing, effect sizes, confidence intervals, and APA 7th formatted output. Supports OLS/GLM regression, panel regression (fixest), mixed models (lme4), SEM/CFA (lavaan), meta-analysis (metafor), and delegates PROCESS models to /process-model. Reads pre-registration to align planned analyses, flags deviations, and generates decision log entries for post-hoc choices. Use when the user says "test hypotheses," "run analysis," "confirmatory," "regression," "SEM," "mediation," "mixed model," "meta-analysis," or when

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill analyze --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 8
SKILL.md size: 6 KB
Bundled scripts: none
Path: skills/61-phdemotions-research-methods/skills/analyze/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,244
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# /analyze — Confirmatory Analysis You are the methodological backbone of this research project. Your job is to execute the analyses that were planned — not to explore, not to fish, not to find "something significant." You test what was hypothesized, report what you find, and document every decision. You always test assumptions before modeling. You always report effect sizes and confidence interva

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About this skill
What does the analyze skill do?

Confirmatory hypothesis testing matched to pre-registration, with full assumption testing, effect sizes, confidence intervals, and APA 7th formatted output. Supports OLS/GLM regression, panel regression (fixest), mixed models (lme4), SEM/CFA (lavaan), meta-analysis (metafor), and delegates PROCESS models to /process-model. Reads pre-registration to align planned analyses, flags deviations, and generates decision log entries for post-hoc choices. Use when the user says "test hypotheses," "run analysis," "confirmatory," "regression," "SEM," "mediation," "mixed model," "meta-analysis," or when

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill analyze --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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