amj-data-analysis
Use when running and reporting the statistical analysis for an Academy of Management Journal (AMJ) manuscript — measurement validity, common-method bias, the right estimator (HLM, SEM, panel, experiments), endogeneity, and robustness. Executes and reports the analysis; it does not design the study (amj-methods) or frame the contribution (amj-contribution-framing).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill amj-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 & Validity (amj-data-analysis) ## When to trigger - Data are collected and it is time to estimate and report - You are unsure whether your estimator matches your design (nested data, latent constructs, panel) - Reviewers will probe measurement validity, common-method bias, or endogeneity - Interaction/mediation effects need correct testing and reporting - A reviewer says "the analysis does not support the inference" or "validity is not established" ## Establish measurement before estimation AMJ reviewers expect the measurement model to be defended first: - **Reliability**: Cronbach's alpha and/or composite reliability for each multi-item scale. - **Confirmatory factor analysis (CFA)**: report fit (e.g., CFI, TLI, RMSEA, SRMR) and show the hypothesized factor structure fits better than plausible alternatives (one-factor, combined-factor models). - **Convergent & discriminant validity**: AVE per construct; AVE > inter-construct squared correlations (or HTMT). Report the correlation matrix with reliabilities on the diagonal. - **Aggregation** (multilevel): justify with ICC(1), ICC(2), and r_wg(j) before aggregating to a higher level. - **Qualitative analysis**: where t
- When to trigger
- Establish measurement before estimation
- Choose the estimator that matches the design
- Common-method bias (CMB)
- Reporting mediation, moderation, and effect sizes
- Robustness
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Output format
What does the amj-data-analysis skill do?
Use when running and reporting the statistical analysis for an Academy of Management Journal (AMJ) manuscript — measurement validity, common-method bias, the right estimator (HLM, SEM, panel, experiments), endogeneity, and robustness. Executes and reports the analysis; it does not design the study (amj-methods) or frame the contribution (amj-contribution-framing).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill amj-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.