JSM2023
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Topic-Contributed Paper Session

Recent Advances in Statistical Modeling and Machine Learning for Dependent Data in Official Statistics and Survey Methodology

Sun, Aug 6, 4:00 PM
Scott HolanChair
Survey Research Methods Section

3 Presentations

A SOCIO-DEMOGRAPHIC LATENT SPACE APPROACH TO SPATIAL DATA WHEN GEOGRAPHY IS IMPORTANT BUT NOT ALL-IMPORTANT
4:05 PM - 4:25 PM
Saikat Nandy (University of Missouri)
Co-authors: Scott Holan (University of Missouri/U.S. Census Bureau), Michael Schweinberger (The Pennsylvania State University)
Bayesian Unit-level Models for Longitudinal Survey Data under Informative Sampling with Application to the Household Pulse Survey
4:25 PM - 4:45 PM
Daniel Vedensky (University of Missouri)
Co-authors: Paul Parker, Scott Holan (University of Missouri/U.S. Census Bureau)
Generating differentially private, tract-level synthetic data for births in Pennsylvania
4:45 PM - 5:05 PM
Harrison Quick
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