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Activity Number:
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22
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Type:
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Contributed
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Date/Time:
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Sunday, July 29, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #310240 |
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Title:
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Selected Bayesian Inference for Correlated Binary Data
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Author(s):
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Patricia Bahnsen*+
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Companies:
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Stephen F. Austin State University
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Address:
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SFA Station Box 13040, Nacogdoches, TX, 75962,
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Keywords:
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Bayesian methods ; correlated binary data ; structural zero model ; bivariate binomial model
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Abstract:
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Correlated binary measurements can occur in a variety of practical contexts and afford interesting statistical modeling challenges. In order to model the separate probabilities for each measurement we must somehow account for the relationship between them. Here we consider Bayesian models for three different prior structures using likelihoods representing the data in the form of a 2 ? 2 table. To do so, consider the data as counts resulting from two correlated binary measurements: the onset of diabetic retinopathy and the onset of diabetic nephropathy. We compare resulting posterior distributions from a Jeffreys' prior, independent beta priors, and conditional beta priors, based on a structural zero likelihood model and the bivariate binomial model.
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