Agent skill · Data & Analytics

commres-data-analysis

Use when executing and reporting the analysis for a Communication Research (CR) manuscript so it survives expert, double-anonymized review — ANOVA/regression/SEM, mediation/moderation with honest uncertainty, reliability, and APA statistical reporting. Guides analysis norms; it does not fabricate results.

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

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

Facts
Files in the skill folder: 1
SKILL.md size: 7 KB
Bundled scripts: none
Path: Communication-Research-Skills/skills/commres-data-analysis/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

# Data Analysis (commres-data-analysis) CR reviewers are quantitatively sophisticated, and the journal expects **APA-style statistical reporting** (effect sizes and standard deviations, not stars alone). Analyze as if your numbers will be scrutinized — because they will. This skill covers execution and reporting norms; design decisions live in `commres-research-design`, and deposit live in `commres-transparency-and-data`. ## When to trigger - Running main and supporting analyses; building the Results section - A reviewer asked for robustness, an alternative specification, or a mediation re-analysis - Reconciling preregistered vs. exploratory analyses - Making the analysis reproducible before deposit ## Analysis norms CR expects 1. **APA statistical reporting.** Report **effect sizes** (d, η²ₚ, R², standardized β) and dispersion (SDs, CIs), test statistics with df, and exact p where feasible — not significance stars alone. 2. **Right model for the design.** ANOVA/ANCOVA for factorial experiments; OLS/logistic regression with proper controls; **SEM/CFA** for latent constructs; **multilevel models** for nested data (e.g., messages within participants, students within classrooms). 3. *

What's inside
Steps it walks through
  1. When to trigger
  2. Analysis norms CR expects
  3. Computational / text-as-data specifics
  4. Reproducibility while you work (not at the end)
  5. Execution bridge (StatsPAI / Stata MCP)
  6. Anti-patterns
  7. Evidence pass for Communication Research
  8. Output format
  9. Supplementary resources
More from Awesome-Journal-Skills
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About this skill
What does the commres-data-analysis skill do?

Use when executing and reporting the analysis for a Communication Research (CR) manuscript so it survives expert, double-anonymized review — ANOVA/regression/SEM, mediation/moderation with honest uncertainty, reliability, and APA statistical reporting. Guides analysis norms; it does not fabricate results.

How do I install it?

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

Keep going