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Using Time to Event Models for Prediction and Inference


John Wallace, Founder and CEO, DataSong
Tess Nesbitt, Senior Consultant, Statistician PhD, DataSong

Companies are doing a better and better job of collecting data that explains why consumers behave the way they do. These diverse data sets cause us to rethink some of the workhorse algorithms for data analysis. Specifically, the traditional binary response model leaves much room for improvement in how it embraces time. Cross–sectional models allow much rich data to fall through the cracks. We’ll discuss real-world scenarios and how to better use data with time to event modeling.

This session will cover:

  • Several business scenarios where time to event modeling makes better use of rich data.
  • Time to event models for prediction
  • Time to event models for inference
  • RevoScale functions used for data analysis