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devpsych-data-analysis
Use when analyzing and reporting results for a Developmental Psychology (APA) manuscript. The journal expects analyses that model developmental change correctly — growth-curve/multilevel/SEM, mediation/moderation, measurement invariance — with effect sizes and confidence intervals, JARS-compliant disclosure, and a clear confirmatory/exploratory split. Guides analysis norms; it does not fabricate results.
Developmental-Psychology-Skills/skills/devpsych-data-analysis/SKILL.md
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# Data Analysis (devpsych-data-analysis)
Developmental Psychology holds analyses to a developmental and a credibility standard at once: the model
must actually capture **change** (not just a cross-sectional snapshot), and reporting must meet **JARS** —
**effect sizes with confidence intervals**, full disclosure, and a clean **confirmatory vs. exploratory**
split. The most common fatal error is interpreting trajectories without first establishing that the
construct is measured the same way across ages.
## When to trigger
- Fitting growth-curve / multilevel / SEM models, or mediation/moderation of developmental effects
- A reviewer asked for measurement invariance, effect sizes, intervals, or attrition handling
- Reconciling preregistered developmental hypotheses with exploratory trajectory findings
- Preparing analysis scripts and a data dictionary for deposit