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Executes and reports empirical analysis for MIS Quarterly manuscripts across behavioral IS, economics-of-IS, design science, and qualitative traditions, including transparency materials.
How this skill is triggered — by the user, by Claude, or both
Slash command
/misq-skills:misq-data-analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- Data are collected (or the artifact is built) and it is time to estimate, evaluate, and report
| Tradition | What to report |
|---|---|
| Behavioral | Reliability (alpha/CR), CFA or PLS measurement model, AVE, discriminant validity (Fornell-Larcker / HTMT); structural paths with effect sizes; mediation via bootstrap CIs; moderation via simple slopes |
| Economics of IS | The identifying variation, parallel-trends/exogeneity evidence, clustered SEs, and a battery of robustness checks (alternative specifications, placebo/event-time tests, sensitivity to assumptions) |
| Design science | Artifact performance against credible baselines on held-out data; ablations; field/A-B or expert evaluation tied to the design propositions; cost/utility discussion |
| Organizational / qualitative | A transparent data structure (codes → themes → dimensions), an audit trail, and representative quotations so the path from raw data to constructs is traceable |
IS reviewers expect the measurement model first. PLS-SEM is common in IS for predictive/formative models; covariance-based SEM for theory-testing with reflective constructs — justify the choice. Report reliabilities, AVE, and discriminant validity, and address common-method bias beyond a single-factor test (marker variable, unmeasured method factor, or showing interactions survive). Then report structural paths with effect sizes, not just significance.
Lead with the identification logic, then stress-test it: alternative specifications, placebo and event-study plots, sensitivity to the key assumption, and clustering that matches the data structure. Report magnitudes and their economic meaning, not just stars.
Demonstrate utility for the real problem: benchmark against the baselines a skeptic would name, run ablations to show which design principles matter, and connect each result back to a design proposition. Where possible, evaluate in a realistic field setting.
MISQ's research-transparency policy is genre-appropriate, not a single template. Document the study's design, data, and analysis to the standard of your tradition, and include procedures and/or code sufficient to permit replication. The transparency commitment is declared and uploaded at submission (Step 2, Miscellaneous). Consider replication badges and the AIS Transactions on Replication Research collaboration. Plan code/data sharing within confidentiality and platform terms.
【Tradition & analysis】SEM / DiD-IV-RD / artifact eval / qualitative
【Validity or identification】measurement + CMB / identification + robustness / baselines + ablations
【Effect sizes / utility】magnitudes and meaning
【Transparency package】procedures/code for replication: ready/gaps
【Next step】misq-contribution-framing
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin misq-skillsRuns and reports empirical analysis for JAIS manuscripts: SEM measurement/structural models, causal identification, artifact evaluation, or qualitative data structure.
Matches research design to MIS Quarterly manuscript tradition: behavioral, economics-of-IS, design science, or qualitative. Plans evaluation strategies and guards against validity threats.
Executes and stress-tests econometric, SEM/PLS, analytical-model, or ML analyses for JMIS manuscripts. Handles identification, endogeneity, construct validity, and robustness checks.