Introduction to Survival Analysis Using Empirical Hazards

Duration: 2.0 days

Audience

This Level I course is designed for anyone who wants to learn about applying time-to-event analysis to business problems, including business managers, SAS programmers, and programmers using other software. Statisticians may also find the course useful, although the content is focused on business solutions rather than statistical rigor.

Course Description

This course introduces survival analysis in the context of business data mining. The focus is on understanding customer behaviors that have a time-to-event component. Understanding how long a customer will remain active is the first step in calculating the future value of that customer. Two data characteristics, discrete time and large volume, make it possible to estimate hazards without making restrictive assumptions about the underlying distribution or form or the hazard function. Empirical hazards provide a window on customer behavior that is useful in itself and also provides the basis for calculating survival curves.

Prerequisites

There are no formal prerequisites. Some familiarity with SAS DATA step programming is helpful for understanding the sample code that will be presented. The class exercises require very little programming.

Course Contents

Uses of Survival Analysis
Empirical Probability Estimates Based on Counting
Point Estimation of Hazards
Calculating Survival from Hazards and Hazards from Survival
Incorporating Additional Explanatory Variables
Competing Risks
Dealing with Left Truncation
Additional Uses for Time Windows
Building a Basic Forecasting System
Explanatory Variables that Vary in Time
Alternate Approaches to Hazard Estimation

Software Addressed

This course addresses the following software product(s): SAS/STAT.

This page was created using SAS software.