popdevr-data-analysis
Use when executing and reporting the analysis for a Population and Development Review (PDR, Wiley / Population Council) manuscript so it survives expert, double-anonymized review — correct rate construction, honest uncertainty, and demographic methods done right, with the development/policy meaning of each quantity made clear. Guides analysis and reporting norms; it does not fabricate results.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-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 (popdevr-data-analysis) PDR reviewers are expert demographers *and* development scholars, and the journal expects analyses that are reproducible and interpretable to a broad readership. Analyze as if a methodologist will re-derive your rates and an economist will ask what each number means for development — because both may. This skill covers execution and reporting norms; method choice lives in `popdevr-research-design`. ## When to trigger - Constructing rates and life tables; building the results section - Running a decomposition, event-history, APC, or projection analysis - A reviewer asked for robustness, sensitivity, or alternative specifications - Making the analysis reproducible and its development meaning explicit before deposit ## Analysis norms PDR expects 1. **Get the denominators right.** Exposure (person-years), the correct base population, and age/period alignment are where demographic analyses live or die. Document how rates were built. 2. **Report uncertainty honestly.** Confidence/credible intervals for rates, life-expectancy contributions, projection scenarios, and derived quantities — not just point estimates or stars. Bootstrap or delta-method in
- When to trigger
- Analysis norms PDR expects
- Demographic and comparative computation specifics
- Reproducibility while you work (not at the end)
- Execution bridge (StatsPAI / Stata MCP)
- Anti-patterns
- Evidence pass for PDR
- Output format
- Supplementary resources
What does the popdevr-data-analysis skill do?
Use when executing and reporting the analysis for a Population and Development Review (PDR, Wiley / Population Council) manuscript so it survives expert, double-anonymized review — correct rate construction, honest uncertainty, and demographic methods done right, with the development/policy meaning of each quantity made clear. Guides analysis and reporting norms; it does not fabricate results.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-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.