misq-data-analysis
Use when running and reporting the empirical core of a MIS Quarterly manuscript — measurement and structural models (PLS/CB-SEM) for behavioral IS, causal identification and robustness for economics-of-IS, artifact evaluation for design science, or trustworthiness for qualitative IS — and assembling the genre-appropriate transparency materials. Executes/reports the analysis; it does not design the study (misq-methods) or frame the contribution (misq-contribution-framing).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill misq-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, Evaluation & Transparency (misq-data-analysis) ## When to trigger - Data are collected (or the artifact is built) and it is time to estimate, evaluate, and report - A reviewer probes measurement validity, identification, artifact utility, or replicability - You must prepare the pluralistic transparency materials uploaded at submission ## Analyze by tradition — there is no single MISQ estimator | 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 → dimen
- When to trigger
- Analyze by tradition — there is no single MISQ estimator
- Behavioral IS: defend measurement before structure
- Economics of IS: make the causal claim earn its keep
- Design science: evaluate the artifact, not just the math
- Assemble the pluralistic transparency materials
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Output format
What does the misq-data-analysis skill do?
Use when running and reporting the empirical core of a MIS Quarterly manuscript — measurement and structural models (PLS/CB-SEM) for behavioral IS, causal identification and robustness for economics-of-IS, artifact evaluation for design science, or trustworthiness for qualitative IS — and assembling the genre-appropriate transparency materials. Executes/reports the analysis; it does not design the study (misq-methods) or frame the contribution (misq-contribution-framing).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill misq-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.