pharmacoepidemiology
De la autor
Reason about pharmacoepidemiologic study design for causal inference from real-world data — choosing active comparator new-user designs, emulating target trials, avoiding immortal time bias, handling time-varying confounding with marginal structural models, and selecting propensity score methods. Use when the user asks to design a drug safety or effectiveness study, choose between propensity score matching vs weighting vs stratification, emulate a target trial, handle immortal time bias, apply marginal structural models, assess unmeasured confounding with E-values, select an active comparator, define a new-user cohort, or evaluate a pharmacoepidemiology study design. Triggers include "active comparator", "new-user design", "target trial emulation", "immortal time bias", "propensity score matching", "IPTW", "marginal structural model", "confounding by indication", "E-value", "negative control outcomes", "quantitative bias analysis", "time-varying confounding", "prevalent user bias", "washout period", "landmark
Instalare
npx skills add awslabs/hcls-agent-skills --skill pharmacoepidemiology -a claude-code
Se instalează în .claude/skills/pharmacoepidemiology/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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