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Activity Number:
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615
- Bayesian Methods for Complex Survey Designs and Data
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 3, 2017 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract #323496
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View Presentation
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Title:
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Bayesian Analysis of Survey Data with Sampling Weights
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Author(s):
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Luis Leon Novelo* and Terrance Savitsky
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Companies:
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University of Texas-Health Science Center At Houston-School of Public Health and U.S. Bureau of Labor Statistics
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Keywords:
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Informative Sampling ;
pseudolikelihood ;
Sampling weights ;
Survey data
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Abstract:
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Bayesian estimation is increasingly popular for performing model based inference to support policymaking. These data are often collected from surveys under informative sampling designs where subject inclusion probabilities are designed to be correlated with the response variable of interest. Sampling weights constructed from marginal inclusion probabilities are typically used to form an exponentiated pseudo likelihood that adjusts the population likelihood for estimation on the sample. We propose an alternative adjustment based on a Bayes rule construction that simultaneously performs weight smoothing and estimates the population model parameters in a fully Bayesian construction. We compare performances between the two approaches on synthetic data.
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Authors who are presenting talks have a * after their name.
