Applying Survival Analysis for Business Time-to-Event Problems
Duration: 2.0 days CEU: 1.2
Presented by Michael J. A. Berry or Gordon S. Linoff, founders of Data Miners, Inc. and co-authors of Data Mining Techniques and Mastering Data Mining
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.
Learn how to
- identify appropriate opportunities for applying survival analysis techniques
- estimate how long a customer will remain active
- measure competing risks in survival analysis modeling.
Who should attend
Business analysts and managers, programmers, and statisticiansPrerequisites
There are no formal prerequisites. A background in business analysis, statistics, or mathematics is helpful but is not essential. The class exercises utilize SAS Enterprise Guide and some programming code is shown. Familiarity with SAS Enterprise Guide or with SAS programming is not required.Course Contents
Introduction- course introduction
- history and background of survival analysis
- visualizing survival
- introduction to data sets used in the class
- introduction to SAS Enterprise Guide
- why empirical hazards
- visualizing the hazard calculation
- the hazard calculation
- defining the start and the stop
- censoring
- tracking survival from one day of starts
- calculating and visualizing survival for all customers
- averaging hazards
- retention versus survival
- quantifying survival
- introduction to covariates
- stratification for time-zero covariates
- Cox proportional hazards regression
- time-zero covariates whose effects change
- creating the right covariates
- risks compete for customers
- conditional hazards and conditional survival
- defining left truncation
- fixing left truncation by filtering
- fixing left truncation with time windows
- overview
- changes in survival over time
- seasonal effects and policy changes
- scoring survival models
- forecasting for new starts
- forecasting for existing customers
- forecasting all customers
- time-varying versus time-zero covariates
- the cohort approach
- direct hazard estimation for one-time events
- the Cox proportional hazards approach
- representing repeating events
- modeling the time to next event
- modeling time to nth event
- fully parametric models
- semi-parametric models
- flexible hazard models
Software Addressed
This course addresses the following software product(s): SAS Enterprise Guide.Course Materials
Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.U.S. Schedule
| 14AUG2008 San Francisco, CA 17NOV2008 Miami, FL | 08OCT2008 Boston, MA 18DEC2008 Atlanta, GA | 20OCT2008 Rockville, MD |
Check for additional and updated schedule information online at support.sas.com/courses/bisa.html.