From ajps-skills
Guides reproducible data analysis and reporting for AJPS manuscripts, covering uncertainty, robustness, heterogeneity, inference, and reproducibility norms.
How this skill is triggered — by the user, by Claude, or both
Slash command
/ajps-skills:ajps-data-analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
AJPS reviewers are methodologically sophisticated, and after acceptance an **independent third-party
AJPS reviewers are methodologically sophisticated, and after acceptance an independent third-party
verifier re-runs your code against the numbers in the main text before the article is published (see
ajps-replication-and-verification). Analyze as if both facts are true — because they are. This skill
covers execution and reporting; design choices live in ajps-research-design.
renv.lock / requirements.txt / logged ssc/net installs).| Question the referee asks | Pass condition | Fix if it fails |
|---|---|---|
| Does the estimator recover the stated estimand? | Estimand named; estimator matches | Name the target quantity before the table |
| Is inference at the right level? | Clustered at assignment/sampling level | Re-cluster; wild-cluster bootstrap if few clusters |
| Will the verifier's re-run match the printed numbers? | Master script regenerates every exhibit | Script everything; set seeds; pin versions |
A survey experiment tests whether a co-partisan endorsement raises policy support. The pre-analysis plan names the estimand (ITT on a 0-100 scale), the primary contrast, and one moderator (political knowledge). Result: +7.4 points (95% CI 3.1-11.7), randomization-inference p = 0.004 (illustrative). A knowledge interaction that was not pre-specified as confirmatory goes to an exploratory subsection, flagged, with a multiple-comparison note. Every number is emitted by one seeded master script, so the AJPS verifier's re-run reproduces the main-text figures exactly.
Calibration anchor: AJPS's independent verifier re-runs deposited code against the main-text numbers before publication, so "it works on my machine" is not enough — confirm the live verification wording against the journal's current guidelines.
【Main estimate】magnitude + interval + substantive meaning
【Identification check】(per research-design) result
【Robustness】specs that could break it -> what held
【Heterogeneity】pre-specified? MHT-adjusted?
【Registered vs exploratory】clearly separated?
【Reproducible】master script + seeds + pinned versions, numbers match? [Y/N]
【Next】ajps-tables-figures
../../resources/external_tools.md — estimation, inference, and text-as-data packages../../resources/official-source-map.md — third-party verification of numerical resultsnpx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin ajps-skillsGuides analysis and reporting for APSR manuscripts to survive expert double-anonymous review. Covers honest uncertainty, robustness, heterogeneity, and reproducibility.
Guides reproducible data analysis for JOP manuscripts: uncertainty reporting, robustness checks, and code that passes replication analyst review.
Guides analysis reporting for BJPS manuscripts: honest uncertainty, robustness checks, heterogeneity, and reproducibility. Use for main and supplementary analyses.