Individual skill
jpart-data-analysis
Use when executing and reporting the analysis for a Journal of Public Administration Research and Theory (JPART) manuscript so it survives expert, double-blind review and the journal's mandatory data-and-code release. Covers honest uncertainty, robustness, and the PA-specific traps (common-method bias, selection). Guides analysis norms; it does not fabricate results.
Journal-of-Public-Administration-Research-and-Theory-Skills/skills/jpart-data-analysis/SKILL.md
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- Last checked
- Nov 9, 2026
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- Repository last updated
- Sep 27, 2026
- License
- MIT
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# Data Analysis (jpart-data-analysis)
JPART reviewers are methodologically sophisticated public-management scholars, and the journal **requires
authors to release the data and software code** underlying the paper as a condition of publication (see
`jpart-transparency-and-data`). Analyze as if a referee will re-run the code — because the materials are
public. This skill covers execution and reporting; design lives in `jpart-research-design`.
## When to trigger
- Running main and supporting analyses; building the results section
- A reviewer asked for robustness, heterogeneity, or alternative specifications
- Reconciling preregistered vs. exploratory analyses
- Making the analysis reproducible before the mandatory data/code deposit
