statistical-modeling
Use when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data. Guides the process (assumptions, estimation, reporting, diagnostics) without forcing a fixed method list.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Statistical Modeling ## Overview This skill defines the process for statistical modeling in empirical research. It is method-agnostic and field-agnostic — the appropriate method for a research question comes from the data and the estimand, not from a fixed list. Reference files organized by method family (cross-section, panel, causal inference, time series) offer starting points, but they are no
What does the statistical-modeling skill do?
Use when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data. Guides the process (assumptions, estimation, reporting, diagnostics) without forcing a fixed method list.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling --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.