Using Survival Analysis in RStat
By Ali-Zain Rahim

Information Builders has made multiple enhancements in version 1.2 of WebFOCUS RStat, our business intelligence and predictive analytics environment. Those enhancements include new modeling techniques, scoring routines, data manipulation capabilities, and performance and usability optimization. The new modeling techniques are in the branch of statistics called “survival analysis.”

Survival analysis is a collection of methods for analyzing the occurrence and timing of an event based on the historical survival or event data. Survival analysis is a branch of statistics that in its basic form deals with death in biological organisms and failure in mechanical systems. In fact, survival analysis is just another name for time-to-event analysis. The key to survival analysis techniques is that they are explicitly designed to deal with missing data problems and time-dependent variables that predict the outcome under study.

The uses in the survival analysis of today vary quite a bit. Applications now include time until onset of disease, time until stock market crash, time until equipment failure, time until earthquake, and so on. The best way to define such events is simply to realize that these events are a transition from one discreet state to another at an instantaneous moment in time. Of course, the term "instantaneous," which may be years, months, days, minutes, or seconds, is relative and has only the boundaries set by the researcher.

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