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jpart-data-analysis

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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.

When to use

• Running main and supporting analyses
• Building the results section
• Addressing reviewer requests for robustness or heterogeneity
• Reconciling preregistered vs. exploratory analyses
• Making the analysis reproducible before data/code deposit
• Reporting uncertainty and effect magnitude
• Confronting PA-specific threats like common-method bias
• Validating constructs and reporting reliability

When not to use

• Fabricating results
• Research design

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