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Invited Paper Session

Using Machine Learning & Data Science Methods to Improve Model Assisted Estimation & Survey Design

Wed, Aug 9, 10:30 AM

Morgan EarpOrganizerKatherine ThompsonChair

No Additional Sponsor co: No Additional Sponsorco: Survey Research Methods Section

5 Presentations

Design Consistent Bayesian Tree Models

10:35 AM - 10:50 AM

Daniell Toth (US Bureau of Labor Statistics)

Treatment of Unit Nonresponse in Surveys Through Regression Trees

10:50 AM - 11:05 AM

David Haziza (University of Ottawa)

Machine Learning and Parametric Modeling Techniques for Informing Responsive Survey Design Strategies

11:05 AM - 11:20 AM

Brady West (Institute for Social Research)

Machine Learning for Model-Based Weighting Methods with Complex Nonresponse in the American Community Survey

11:20 AM - 11:35 AM

Darcy Morris (U.S. Census Bureau)

Co-authors: Joseph Kang (US Census Bureau), Patrick Joyce (US Census Bureau), Isaac Dompreh

Using Machine Learning for Nonresponse Adjustment in the National Health Interview Survey (NHIS)

11:35 AM - 11:50 AM

Morgan Earp (National Center for Health Statistics)

Co-authors: Benjamin Zablotsky (National Center for Health Statistics), Lindsey Black (National Center for Health Statistics), Jonaki Bose (NCHS), Matthew Bramlett (National Center for Health Statistics), James Dahlhamer (National Center for Health Statistics)

Discussant

Kelly McConville (Harvard University)

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