jedpsych-data-analysis
Use when analyzing and reporting results for a Journal of Educational Psychology manuscript. JEP expects analyses that respect nesting (multilevel/SEM/growth models), report educationally meaningful effect sizes with confidence intervals, test mechanisms (mediation/moderation), and follow JARS with full disclosure. Guides analysis norms; it does not fabricate results.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jedpsych-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 (jedpsych-data-analysis) The Journal of Educational Psychology holds analyses to the standards of a rigorous psychological research journal *operating in nested educational settings*. The recurring requirements are: **model the nesting** (students in classes in schools), report **effect sizes with confidence intervals** that are **educationally interpretable**, test the **mechanism** (mediation/moderation), and disclose fully under **JARS**. Analysis scripts and data are expected to be shareable and reproducible. ## When to trigger - Running and reporting the main and supporting analyses - A reviewer asked for multilevel modeling, effect sizes, mechanism tests, or disclosure - Reconciling preregistered analyses with exploratory follow-ups - Preparing analysis scripts and a codebook for deposit ## Reporting norms JEP expects 1. **Respect the nesting.** Use multilevel (hierarchical linear) models, SEM, or growth models that account for students nested in classrooms/schools. Cluster-robust or random-effects inference is expected; ignoring clustering deflates standard errors and is a standard JEP rejection reason. 2. **Educationally meaningful effect sizes + uncertainty
- When to trigger
- Reporting norms JEP expects
- Robustness and missing data
- Worked micro-example (illustrative numbers)
- Analysis-stage reviewer pushback and the venue fix
- Calibration anchors
- Execution bridge (StatsPAI / Stata MCP)
- Anti-patterns
- Output format
- Supplementary resources
What does the jedpsych-data-analysis skill do?
Use when analyzing and reporting results for a Journal of Educational Psychology manuscript. JEP expects analyses that respect nesting (multilevel/SEM/growth models), report educationally meaningful effect sizes with confidence intervals, test mechanisms (mediation/moderation), and follow JARS with full disclosure. Guides analysis norms; it does not fabricate results.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jedpsych-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.