Agent skill · Data & Analytics

jpsp-study-design

Use when designing the multi-study package for a Journal of Personality and Social Psychology (JPSP) manuscript — sequencing studies, powering each one, choosing experimental / longitudinal / dyadic designs, and planning preregistration. Designs the study set; it does not collect or fabricate data.

brycew6m4,252★ · +31/wk · 3 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jpsp-study-design --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 7 KB
Bundled scripts: none
Path: Journal-of-Personality-and-Social-Psychology-Skills/skills/jpsp-study-design/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 909 · +31 this week
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Study Design — The Multi-Study Package (jpsp-study-design) This is the skill that most distinguishes JPSP from short-report journals. A JPSP paper is a **coherent set of related studies** built to test a theory, not a single experiment. The package must *converge*: each study should add something the previous one could not establish, and the set should withstand the question "could one study break the whole story?" ## When to trigger - Planning the sequence and roles of studies in the package - Powering each study and the package as a whole - Choosing designs (experiment, survey, longitudinal, dyadic/APIM, intensive-longitudinal, archival) - Deciding what to preregister and what is exploratory ## Designing the package 1. **Give every study a job.** A common arc: **establish** the effect → test the **mechanism** (mediation/process) → probe **boundary conditions / moderators** → demonstrate **generalization** (population, context, method). Avoid a pile of near-identical replications. 2. **Triangulate methods.** Combine, e.g., an experiment (causal) with a field/longitudinal study (external validity) so the package is robust to any single design's weaknesses. 3. **Mind the section's

What's inside
Steps it walks through
  1. When to trigger
  2. Designing the package
  3. Execution bridge (StatsPAI / Stata MCP)
  4. Anti-patterns
  5. Post-credibility-revolution power calibration
  6. Worked vignette: powering a three-study ASC package
  7. Output format
  8. Supplementary resources
More from Awesome-Journal-Skills
All skills →
About this skill
What does the jpsp-study-design skill do?

Use when designing the multi-study package for a Journal of Personality and Social Psychology (JPSP) manuscript — sequencing studies, powering each one, choosing experimental / longitudinal / dyadic designs, and planning preregistration. Designs the study set; it does not collect or fabricate data.

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jpsp-study-design --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.

Keep going