DeMets Lecture 2 with Tom Louis of Johns Hopkins Bloomberg School of Public Health
Improved Small Domain Estimation via Compromise Regression Weights
Event Details
Date
Friday, November 13, 2026
Time
Noon-1 p.m.
Location
Description
Shrinkage estimation of small domain parameters typically combines a noisy direct estimate with a more stable regression estimate. However, if the regression model is misspecified, the optimal (MLE) estimate of regression parameters can degrade performance. Jiang et all addressed this with the Observed. Best Predictor (OBP). Dr. Louis introduces a class of empirically informed regression weights that are convex combination of the MLE and OBP values-a Compromise Best Predictor (CBP).
Cost
Free
Contact
Accessibility
We value inclusion and access for all participants and are pleased to provide reasonable accommodations for this event. Please email juan.caicedo@wisc.edu to make a disability-related accommodation request. Requests should be made by Friday, October 30, 2026, though reasonable effort will be made to support late accommodation requests.