jibs-data-analysis
Use when running and reporting the empirical analysis for a Journal of International Business Studies (JIBS) manuscript — cross-national measurement equivalence, common-method-variance checks, the right multilevel/dynamic-panel estimator, endogeneity and dynamic-endogeneity identification, and robustness aligned to the JIBS methods-editorial canon. Executes and reports; it does not design the study (jibs-methods) or frame the contribution (jibs-contribution-framing).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jibs-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 & Cross-National Validity (jibs-data-analysis) ## When to trigger - Cross-country or multilevel data are collected and it is time to estimate and report - You are unsure your estimator matches nesting (individuals in firms in countries) or a process design - Reviewers will probe measurement equivalence, CMV, or (dynamic) endogeneity - A reviewer cites a JIBS "From the Editors" methods editorial against your analysis ## Establish cross-national measurement equivalence first At JIBS, because constructs travel across countries and cultures, **measurement equivalence is a first-order review concern**, not an afterthought. Before testing hypotheses: - **Reliability & CFA.** Report reliability (alpha/composite reliability) and a confirmatory factor analysis with fit (CFI, TLI, RMSEA, SRMR). - **Measurement invariance.** Run multi-group CFA and report **configural → metric → scalar** invariance across countries; if scalar fails, report partial invariance or the alignment method and discuss what cross-country comparisons remain defensible. - **Construct & discriminant validity.** AVE per construct; AVE > inter-construct squared correlations (or HTMT). Report the correlation
- When to trigger
- Establish cross-national measurement equivalence first
- Match the estimator to the cross-country/multilevel design
- Common-method variance (CMV) — an active JIBS gatekeeper
- Endogeneity and "dynamic endogeneity"
- Reporting & robustness
- Execution bridge (StatsPAI / Stata MCP)
- Output format
- Anti-patterns
What does the jibs-data-analysis skill do?
Use when running and reporting the empirical analysis for a Journal of International Business Studies (JIBS) manuscript — cross-national measurement equivalence, common-method-variance checks, the right multilevel/dynamic-panel estimator, endogeneity and dynamic-endogeneity identification, and robustness aligned to the JIBS methods-editorial canon. Executes and reports; it does not design the study (jibs-methods) or frame the contribution (jibs-contribution-framing).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jibs-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.