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Abstract Details
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Activity Number:
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407
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #301104 |
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Title:
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Modeling Multivariate Binary Data with Copulas Over Partitions
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Author(s):
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Bruce Judson Swihart*+ and Brian Caffo and Ciprian Crainiceanu
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Companies:
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The Johns Hopkins University and The Johns Hopkins University and The Johns Hopkins University
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Address:
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Department of Biostatistics, Baltimore, MD, 21205,
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Keywords:
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Binary outcomes ;
Copulas ;
Marginal likelihood ;
Multivariate Logit ;
Multivariate probit ;
Stable distributions
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Abstract:
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Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood-based models for marginal ?xed effects estimation and interpretation in the analysis of correlated binary data with exchangeable correlation structures. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized random intercept models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.
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