psci-data-analysis
Use when analyzing and reporting results for a Psychological Science manuscript. The journal requires effect sizes with confidence intervals, full disclosure of exclusions/conditions/measures, and a clear confirmatory/exploratory split, with analysis scripts and data shared. Guides analysis norms; it does not fabricate results.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill psci-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 (psci-data-analysis) Psychological Science holds analyses to high credibility standards: **effect sizes with confidence intervals** for major results, **full disclosure** of how the data were handled, and a clean **confirmatory vs. exploratory** separation. Analysis scripts and data are shared and can be checked. ## When to trigger - Running and reporting the main and supporting analyses - A reviewer asked for effect sizes, intervals, robustness, or disclosure - Reconciling preregistered analyses with exploratory follow-ups - Preparing analysis scripts and a data dictionary for deposit ## Reporting norms Psychological Science expects 1. **Effect sizes + uncertainty.** Report a standardized or unstandardized effect size **and a measure of uncertainty (e.g., confidence intervals)** for major results — not just p-values and stars. 2. **Full disclosure (the "21-word-solution" spirit).** Report **how sample size was determined**, **all** data exclusions (and reasons), **all** manipulations/conditions, and **all** measures. Total excluded observations must be stated. 3. **Confirmatory vs. exploratory.** Label preregistered confirmatory analyses separately from exploratory
- When to trigger
- Reporting norms Psychological Science expects
- Robustness
- 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 psci-data-analysis skill do?
Use when analyzing and reporting results for a Psychological Science manuscript. The journal requires effect sizes with confidence intervals, full disclosure of exclusions/conditions/measures, and a clear confirmatory/exploratory split, with analysis scripts and data shared. Guides analysis norms; it does not fabricate results.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill psci-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.