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Activity Number: 433 - SPEED: Applications of Advanced Statistical Techniques in Complex Survey Data Analysis: Small Area Estimation, Propensity Scores, Multilevel Models, and More
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 2:00 PM to 2:45 PM
Sponsor: Survey Research Methods Section
Abstract #333024
Title: Comparing Direct Survey and Small Area Estimates of Health Care Coverage in New York
Author(s): Jeniffer Iriondo Perez* and Rachel Harter and Amang Sukasih
Companies: RTI International and RTI International and RTI International
Keywords: Small Area Estimation; BRFSS; Health Care
Abstract:

The Behavioral Risk Factor Surveillance Survey (BRFSS) is designed to produce estimates for states and large metropolitan areas. For some variables, county-level BRFSS estimates have been produced by others using small area estimation methodology. We generated county-level estimates of the proportion of adults with health insurance coverage (insured rate) using the New York BRFSS data. The goal was to demonstrate the small area estimation (SAE) technique using the readily-available R package BayesSAE. As a validation, we compared the results from BayesSAE with those from OpenBUGS, a well-established software for Bayesian computation. We also compared the model-based estimates with direct design-based estimates.


Authors who are presenting talks have a * after their name.

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