Epidemiology Methods for R

概要

This skill provides a robust framework for epidemiologists and biostatisticians to perform advanced public health analytics using R. It automates the implementation of domain-specific methods including measures of association, incidence rate calculations, and complex regression modeling. Beyond basic statistics, it facilitates modern causal inference techniques such as Directed Acyclic Graphs (DAGs), propensity score matching, and doubly robust estimation. Whether you are designing a cohort study or investigating an active outbreak, this skill offers standardized code patterns to ensure rigorous and reproducible epidemiological research.

主な機能

• Propensity score analysis via matching, IPTW, and Doubly Robust Estimation
• 0 GitHub stars
• Advanced regression modeling including Logistic, Poisson, and Log-Binomial methods
• Standardized incidence rate and SMR calculations with person-time splitting
• Causal inference toolkit featuring DAGs, E-values, and Instrumental Variables
• Study design utilities for sample size and power calculations across various designs

ユースケース

• Generating real-time epidemic curves and attack rates during public health outbreaks
• Analyzing observational data to estimate treatment effects while controlling for confounding
• Calculating sample size requirements for new clinical cohort or case-control studies