Introduction

This workshop teaches you practical skills for research using techniques typically known as "event history analysis." Other names for these techniques include survival analysis, hazard models, or time-to-event analysis. These techniques include a variety of approaches, both parametric and non-parametric, both single and multi-variate. We cover topics such as life tables, Kaplan-Meier estimates, parametric regression models, proportional hazard models, and discrete-time models.

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
• Evaluating if Data can Support Event HistoryAnalysis
• Practical, Hands-on Computing Exercises in R

Sessions

• Session 1 (Mon): Basic Concepts, Data Structures, and Relationship to Life Tables
• Session 2 (Tue): Kaplan-Meier Method
• Session 3 (Wed): Cox Models
• Session 4 (Thu): Parametric Models
• Session 5 (Fri): Discrete-time Models

Comments from Previous Participants