Business Knowledge Series course
Presented by Gordon S. Linoff, co-founder of Data Miners, Inc. and co-author of Data Mining Techniques and Mastering Data Mining
Formats available | Standard Duration (duration can vary, see event schedule for details) | | |
Classroom: |
2.0 days | | |
|
This course addresses SAS Enterprise Guide software.
Introduction- course introduction
- history and background of survival analysis
Tools and Data- visualizing survival
- introduction to data sets used in the class
- introduction to SAS Enterprise Guide
Understanding the World by Counting
Point Estimation of Hazards- why empirical hazards
- visualizing the hazard calculation
- the hazard calculation
- defining the start and the stop
- censoring
Estimating Survival- tracking survival from one day of starts
- calculating and visualizing survival for all customers
- averaging hazards
- retention versus survival
- quantifying survival
The Role of Covariates- introduction to covariates
- stratification for time-zero covariates
- Cox proportional hazards regression
- time-zero covariates whose effects change
- creating the right covariates
Competing Risks- risks compete for customers
- conditional hazards and conditional survival
Left Truncation- defining left truncation
- fixing left truncation by filtering
- fixing left truncation with time windows
Time Windows- overview
- changes in survival over time
- seasonal effects and policy changes
Scoring Survival Models and Forecasting- scoring survival models
- forecasting for new starts
- forecasting for existing customers
- forecasting all customers
Time-Varying Covariates- time-varying versus time-zero covariates
- the cohort approach
- direct hazard estimation for one-time events
- the Cox proportional hazards approach
Repeating Events- representing repeating events
- modeling the time to next event
- modeling time to nth event
Beyond Empirical Hazards- fully parametric models
- semi-parametric models
- flexible hazard models
