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Activity Number:
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186
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2008 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #302170 |
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Title:
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The Connection Between Bayesian- and Resampling-Based Inference in Small-Area Models
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Author(s):
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Snigdhansu Chatterjee*+
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Companies:
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The University of Minnesota
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Address:
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313 Ford Hall, Minneapolis, MN, 55455,
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Keywords:
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Small area ; parametric bootstrap ; Bayesian
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Abstract:
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A general small area model is a hierarchal two stage model, of which special cases are mixed linear models, generalized linear mixed models and hierarchal generalized linear models. Such models naturally lend themselves to both Bayesian and non-Bayesian analysis. In recent times, parametric bootstrap for small area models has become an active field of study. Although resampling techniques like the parametric bootstrap are inherently non-Bayesian, there are some deep connections between resampling and Bayesian analysis. This talk will focus on some of these connections in the context of small area problems.
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