jpsp-data-analysis
Use when analyzing and reporting the multi-study package for a Journal of Personality and Social Psychology (JPSP) manuscript to JARS standard — effect sizes with uncertainty, honest robustness, and an internal meta-analysis that pools effects across studies. Guides analysis and reporting norms; it does not fabricate results.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jpsp-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 & Internal Meta-Analysis (jpsp-data-analysis) JPSP reviewers are methodologically sophisticated and the journal requires **JARS** reporting and **TOP Level 2** transparency. Two things set JPSP analysis apart from short-report work: (1) you are analyzing a **set of studies**, and (2) the section expects you to **integrate across them** — an **internal meta-analysis** is a core move, explicitly prioritized in IRGP guidance. This skill covers execution and reporting; design lives in `jpsp-study-design`. ## When to trigger - Analyzing studies and building the results sections - Pooling effects across your own studies (internal meta-analysis) - A reviewer asked for robustness, mechanism, or alternative-explanation analyses - Reconciling preregistered vs. exploratory analyses ## Analysis norms JPSP expects 1. **Effect sizes with uncertainty.** Report standardized effect sizes and **confidence (or credible) intervals**, not just p-values/stars; state the **substantive magnitude**, per JARS. 2. **Internal meta-analysis across studies.** Pool the comparable effects from all studies (including any reported only in the supplement) into a **random-effects estimate with a fores
- When to trigger
- Analysis norms JPSP expects
- Reproducibility while you work (not at the end)
- Execution bridge (StatsPAI / Stata MCP)
- Anti-patterns
- Reviewer-pushback patterns and the analysis-side fix
- Worked micro-example: pooling a preregistered three-study package
- Output format
- Supplementary resources
What does the jpsp-data-analysis skill do?
Use when analyzing and reporting the multi-study package for a Journal of Personality and Social Psychology (JPSP) manuscript to JARS standard — effect sizes with uncertainty, honest robustness, and an internal meta-analysis that pools effects across studies. 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 jpsp-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.