crim-data-analysis
Use when executing and reporting the analysis for a Criminology (ASC / Wiley) manuscript so it survives expert review — honest uncertainty, robustness, and methods appropriate to crime counts, longitudinal panels, trajectory models, and recidivism survival. Guides analysis norms; it does not fabricate results.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill crim-data-analysis --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.
# Data Analysis (crim-data-analysis) *Criminology* reviewers are methodologically sophisticated and increasingly expect that your results can be reproduced from deposited materials (see `crim-data-and-transparency`). Analyze as if both are true. This skill covers execution and reporting norms; design decisions live in `crim-research-design`. ## When to trigger - Running main and supporting analyses; building the results section - A reviewer asked for robustness, heterogeneity, or alternative specifications - Fitting a trajectory model, fixed-effects panel, count model, or survival model - Making the analysis reproducible before deposit ## Analysis norms Criminology expects 1. **Report uncertainty honestly.** Confidence/credible intervals, not just stars; the **magnitude and substantive meaning** (e.g., incident-rate ratios, predicted counts, change in offending), not just significance. 2. **Right model for crime data.** Counts are over-dispersed and zero-heavy — prefer negative binomial / zero-inflated / hurdle over OLS on raw counts; rates need exposure offsets; rare-event cautions apply. 3. **Within- vs. between-person.** When the theory is developmental, isolate within-individua
- When to trigger
- Analysis norms Criminology expects
- Crime-measurement specifics
- Reproducibility while you work (not at the end)
- Execution bridge (StatsPAI / Stata MCP)
- Anti-patterns
- Estimator choice keyed to the crime outcome (Criminology decision table)
- Worked micro-example: reading a within-person estimate (illustrative)
- Analysis-stage referee pushback (with the Criminology fix)
- Output format
- Supplementary resources
What does the crim-data-analysis skill do?
Use when executing and reporting the analysis for a Criminology (ASC / Wiley) manuscript so it survives expert review — honest uncertainty, robustness, and methods appropriate to crime counts, longitudinal panels, trajectory models, and recidivism survival. Guides analysis norms; it does not fabricate results.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill crim-data-analysis --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/Awesome-Journal-Skills, a repository with 909 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.