jams-data-analysis
Use when running and reporting the analysis for a Journal of the Academy of Marketing Science (JAMS) manuscript — selecting the estimator that matches the design (SEM/PLS, HLM, regression/econometrics, experiments, meta-analysis), reporting effect sizes and uncertainty, and translating estimates into managerial magnitudes. Executes and reports; jams-methods designs the study and jams-contribution-framing states the payoff.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-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 & Reporting (jams-data-analysis) ## When to trigger - Data are collected and it is time to estimate and report - You are unsure whether the estimator matches the design or the data structure - A reviewer says "the analysis does not support the inference" or "report effect sizes" - Significance is reported but the managerial magnitude is missing ## Choose the estimator that matches the design | Design / claim | Estimator | |---|---| | Latent constructs + structural paths (survey) | Covariance-based **SEM** (Mplus / lavaan / AMOS); **PLS-SEM** when prediction or formative constructs dominate | | Nested data (consumers in stores, firms in industries) | **HLM / multilevel** models; random intercepts/slopes; report ICC | | Mediation (process) | Bootstrapped indirect effects (PROCESS / lavaan), **bias-corrected CIs**; report the indirect effect, not just Baron–Kenny steps | | Moderation / moderated mediation | Interaction term + simple slopes; conditional indirect effects (index of moderated mediation) | | Experiment (factorial) | ANOVA / regression; estimated marginal means; planned contrasts; effect sizes per cell | | Panel / observational causal | FE / **DiD** (modern
- When to trigger
- Choose the estimator that matches the design
- JAMS reporting conventions
- Translate every result into a managerial magnitude
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Robustness that targets the design's real threat
- Anti-patterns
- Output format
What does the jams-data-analysis skill do?
Use when running and reporting the analysis for a Journal of the Academy of Marketing Science (JAMS) manuscript — selecting the estimator that matches the design (SEM/PLS, HLM, regression/econometrics, experiments, meta-analysis), reporting effect sizes and uncertainty, and translating estimates into managerial magnitudes. Executes and reports; jams-methods designs the study and jams-contribution-framing states the payoff.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jams-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.