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Activity Number:
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381
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 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 - #310093 |
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Title:
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A Bayesian Method for IRT Model Selection
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Author(s):
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Sherwin Toribio*+
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Companies:
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University of Wisconsin-La Crosse
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Address:
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Mathematics Department, La Crosse, WI, 54601,
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Keywords:
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IRT models ; Bayesian methods ; Bayes Factor ; Hierarchical model ; Gibbs Sampling
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Abstract:
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Item Response Theory (IRT) models are commonly used in educational and psychological testing. These models are mainly used to assess the (latent) abilities of examinees and the effectiveness of the test items in measuring this underlying trait. Several models are currently available for this purpose. In this paper, a Bayesian method to compare different IRT models will be discussed. In particular, the Bayes factor will be employed to determine which model is more appropriate for the data.
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