JSM 2004 - Toronto

Abstract #301232

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Activity Number: 59
Type: Invited
Date/Time: Sunday, August 8, 2004 : 6:00 PM to 7:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #301232
Title: Modeling Survey Nonresponse in Dichotomous Processes
Author(s): Jacob J. Oleson*+ and Chong He
Companies: Arizona State University and University of Missouri, Columbia
Address: Department of Mathematics & Statistics, Tempe, AZ, 85287-1804,
Keywords: incomplete data ; nonignorable ; spatial correlation ; hierarchical Bayes
Abstract:

Sampling units that do not answer a survey may dramatically affect the estimation results of interest. The response may even be conditional on the outcome of interest. If estimates are found using only those who responded, the estimate may be biased, known as nonresponse bias. Our objective is to find estimates of success rates from a survey when there may be nonresponse bias. Often, these success rates may be spatially correlated. The response rates may also be spatially correlated. This is particularly true if response is conditional on the outcome. In a Bayesian hierarchical framework, we examine two approaches for treating nonresponse that account for potential spatial correlations. Spatial dependence is induced by a common latent spatial structure. This methodology is appropriate for many surveys including the American Community Survey, the National Health Interview Study, and the National Health and Nutrition Examination Survey. An example will be presented.

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