Agent skill · Data & Analytics

jmgmt-methods

Use when research design and measurement are the bottleneck for a Journal of Management (JOM) manuscript — matching design to the theoretical claim, construct validity, common-method bias, endogeneity, multilevel structure, and (for meta-analyses) coding/artifact corrections. Designs the study; it does not run the estimation (jmgmt-data-analysis).

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jmgmt-methods --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 8 KB
Bundled scripts: none
Path: Journal-of-Management-Skills/skills/jmgmt-methods/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 909 · +31 this week
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Research Design & Methods (jmgmt-methods) ## When to trigger - The design may not match the theory's level, timing, or causal claim - Data are single-source, single-wave, self-reported (common-method bias risk) - The theory is causal but the design is cross-sectional/correlational - Constructs lack established, validated measures - A meta-analysis needs a defensible coding protocol and artifact-correction plan - A reviewer says "the design cannot test this hypothesis" or "endogeneity is unaddressed" ## Match the design to the claim JOM welcomes **all empirical methods** — survey, experiment, archival panel, multilevel field study, qualitative, and meta-analysis — and judges on *fit and rigor*, not a preferred method. JOM's **research-methods identity** (it explicitly covers research methods and runs methods-focused reviews) means design choices are scrutinized closely. | Theoretical claim | Design that earns it | |-------------------|----------------------| | Causal effect of a manipulable cause | Experiment (lab/online/field), or natural experiment | | Process unfolding over time | Multi-wave panel; longitudinal/lagged design | | Firm/strategy outcome from archival cause | Panel

What's inside
Steps it walks through
  1. When to trigger
  2. Match the design to the claim
  3. Designing against the threats JOM referees punish
  4. Meta-analysis design
  5. Referee pushback mapped to the design fix
  6. Designing a multi-study program
  7. Execution bridge (StatsPAI / Stata MCP)
  8. Checklist
  9. Anti-patterns
  10. Output format
More from Awesome-Journal-Skills
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About this skill
What does the jmgmt-methods skill do?

Use when research design and measurement are the bottleneck for a Journal of Management (JOM) manuscript — matching design to the theoretical claim, construct validity, common-method bias, endogeneity, multilevel structure, and (for meta-analyses) coding/artifact corrections. Designs the study; it does not run the estimation (jmgmt-data-analysis).

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jmgmt-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.

Keep going