jm-methods
Use when choosing and defending the research design for a Journal of Marketing (JM) manuscript — matching a "big tent" method (experiment, field study, survey, secondary data, qualitative) to a substantive marketing question, with field realism and identification in mind. Designs the study; it does not run the estimation (jm-data-analysis) or frame the contribution (jm-contribution-framing).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jm-methods --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.
# Research Design, Big-Tent (jm-methods) ## When to trigger - The question is set and you must choose a design that can actually answer it - A reviewer will ask whether the method supports a *causal* or *managerial* claim - You are deciding between a clean lab experiment and a messier but realer field study - You have secondary (scanner/CRM/financial) data and need an identification strategy ## JM's "big tent" — let the question pick the method JM is methodologically pluralistic: it welcomes **primary data** (experiments, field studies, surveys, interviews, observational data) and **secondary data**, and champions **empirics-first** research grounded in real-world phenomena. No single method is privileged. The design rule at JM is therefore: choose the method that most credibly answers a **substantive** question and supports a **managerially relevant** claim — not the most sophisticated technique. Work centered on mathematical/statistical methods for their own sake is out of scope (route to Marketing Science / JMR); methods here are **servants** of the substantive insight. ## Match design to claim | Substantive claim / data situation | Design | |------------------------------------
- When to trigger
- JM's "big tent" — let the question pick the method
- Match design to claim
- Field realism and managerial validity
- Design for transparency up front
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Output format
What does the jm-methods skill do?
Use when choosing and defending the research design for a Journal of Marketing (JM) manuscript — matching a "big tent" method (experiment, field study, survey, secondary data, qualitative) to a substantive marketing question, with field realism and identification in mind. Designs the study; it does not run the estimation (jm-data-analysis) or frame the contribution (jm-contribution-framing).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jm-methods --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.