Comparing Rates using R: Poisson Regression & Survival Analysis (Applied Examples)
Автор: Stats Clinic
Загружено: 2025-12-30
Просмотров: 19
In this hands-on R lab, we walk through applied modeling approaches for count, rate, and time-to-event data using real-world examples from a longitudinal cohort of resident physicians.
Topics covered include:
Poisson regression for counts vs. rates, including interpretation of ratios and offsets
Choosing and interpreting link functions (identity vs. log)
Introduction to survival analysis concepts
Kaplan–Meier curves (base R and ggplot)
Log-rank tests for group comparisons
Cox proportional hazards models and checking the PH assumption
Designed for learners with basic R knowledge who want practical exposure to regression and survival methods commonly used in epidemiology, clinical research, and public health.
📊 Code-based, interpretation-focused, and grounded in applied data analysis.
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