lancet-statistics
Use to enforce The Lancet's clinical-statistics reporting — confidence intervals over bare P values, a pre-specified primary analysis, intention-to-treat with per-protocol sensitivity, multiplicity control for secondary endpoints, cautious pre-specified subgroup analyses with interaction tests, missing-data handling, and absolute plus relative effects.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill lancet-statistics --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.
# Clinical Statistics (lancet-statistics) ## When to trigger - Results report P values but not confidence intervals or effect sizes. - The primary analysis population (ITT vs per-protocol) is unclear. - Many secondary endpoints or subgroups are reported with no multiplicity/interaction handling. - A **statistical reviewer** is likely (The Lancet uses them) and the analysis is not pre-specified. ## The reporting backbone (every clinical estimate) Each estimate needs: **effect measure + 95% CI + the analysis population + the pre-specified test.** - [ ] **Confidence intervals** for every key estimate — CIs over bare P values; The Lancet de-emphasises isolated significance. - [ ] **Exact P values** (e.g., p=0·013), not "p<0·05," reported alongside CIs, not instead of them. - [ ] **Absolute and relative effects**: report the absolute risk/rate difference *and* the relative measure (RR/OR/HR); add **NNT/NNH** where clinically relevant. - [ ] **Analysis population stated**: ITT as the primary population for superiority RCTs. - [ ] The **test/model named** and matched to outcome type (survival → Cox/log-rank; binary → logistic/risk; count → Poisson/negative binomial; clustered → mixed/GEE)
- When to trigger
- The reporting backbone (every clinical estimate)
- Pre-specification and the primary analysis
- ITT and sensitivity analyses
- Multiplicity and secondary endpoints
- Subgroups — pre-specified and cautious
- Survival and time-to-event
- What the Lancet statistical reviewer expects
- Worked micro-example (illustrative numbers — not real data)
- Reviewer-pushback patterns and the venue-specific fix
- Output format
- Anti-patterns
What does the lancet-statistics skill do?
Use to enforce The Lancet's clinical-statistics reporting — confidence intervals over bare P values, a pre-specified primary analysis, intention-to-treat with per-protocol sensitivity, multiplicity control for secondary endpoints, cautious pre-specified subgroup analyses with interaction tests, missing-data handling, and absolute plus relative effects.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill lancet-statistics --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.