jmr-methods
Use when matching the research design to the claim for a Journal of Marketing Research (JMR) manuscript — experimental design (lab and field), causal identification (IV/DiD/RDD/matching), or structural/analytical estimation. Adapts to JMR's dominant genres and to its journal-level rigor and replication expectations. It designs; jmr-data-analysis executes and reports.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jmr-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 & Identification (jmr-methods) ## When to trigger - The design may not actually support the causal, behavioral, or structural claim - You must choose between a lab experiment, a field experiment, and observational identification - A structural model needs an identification and estimation plan - Reviewers will probe confounds, internal/external validity, or "what identifies this?" ## Match design to the claim by genre ### Behavioral (lab and field experiments) - **Manipulation**: a clean operationalization of the cause, with manipulation and attention checks; pretests to validate stimuli. - **Design**: random assignment; factorial designs for interactions; **process-by-moderation** or measured-vs-manipulated mediation to test the mechanism (not just the effect). - **Field experiments**: a randomized intervention with a real marketing outcome (purchase, click, retention) strengthens external validity; pre-register where feasible. - **Power**: a priori power analysis sized for the **interaction**, not just the main effect; plan multiple studies (lab establishes mechanism; field shows it in market). ### Modeling / econometric (observational and structural) - **Causal
- When to trigger
- Match design to the claim by genre
- Behavioral (lab and field experiments)
- Modeling / econometric (observational and structural)
- Journal-level expectations that shape design
- Execution bridge (StatsPAI / Stata MCP)
- Anti-patterns
- Methods pass for Journal of Marketing Research
- Output format
- Resources
What does the jmr-methods skill do?
Use when matching the research design to the claim for a Journal of Marketing Research (JMR) manuscript — experimental design (lab and field), causal identification (IV/DiD/RDD/matching), or structural/analytical estimation. Adapts to JMR's dominant genres and to its journal-level rigor and replication expectations. It designs; jmr-data-analysis executes and reports.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jmr-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.