Model Rare Events with a Log Link and Handle Zero Counts
WaymoData Scientist · Technical Screen
Last updated
Explain rare-event log-link models, exposure offsets, zero counts, overdispersion, and the difference between counts and binary outcomes.
Model Rare Events with a Log Link and Handle Zero Counts
Explain how a log-form model can be used for rare-event data and why it may be useful. Be precise about whether you are transforming observed outcomes or modeling a mean or rate. Explain how zero observed events are handled, and state the assumptions needed for your proposed model.
Hints
Hint 1
Locate the logarithm: A zero observation does not imply that the model must take log zero.
Follow-up questions
- What changes if the data have more zero counts than a Poisson model predicts?
- How do you compare units observed for different amounts of exposure?
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