Introduction

This workshop teaches methods for analyzing the timing and occurrence of events using techniques commonly known as event history analysis (also called survival analysis, hazard models, or time‑to‑event analysis). Participants learn how to model the risk of events over time while appropriately handling censoring, truncation, and time‑varying covariates. We cover life tables, Kaplan–Meier estimation, parametric survival models, Cox proportional hazards models, and discrete‑time approaches. The workshop emphasizes interpretation of hazard ratios and survival curves, practical hands‑on skills through computing exercises, and strategies for avoiding common errors.

Participants Requirements

• Prior graduate-level statistics course in applied regression analysis.
• Experience with statistical software (R preferred).
• Laptop with R and R Studio installed.

Key Features

• Understanding Concepts of Event History Analysis
• Hands-on Event History Analysis with R Programming
• Evaluating if Event History is Appropriate for Your Research Question

Sessions

• Session 1 (Mon): Basic Concepts, Data Structures, and Relationship to Life Tables, Kaplan-Meier Method
• Session 2 (Tue): Cox Models
• Session 3 (Wed): Parametric Models
• Session 4 (Thu): Discrete-time Models

※ Workshop 3 will be conducted over four days, from Monday through Thursday. The total course hours will be the same as for the other workshops. The detailed timetable is subject to change

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