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" Comparing three estimation methods for the three-parameter logistic IRT model "
Sunil Lamsal
Sheng, Yanyan
Document Type
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Latin Dissertation
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Language of Document
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English
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Record Number
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803837
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Doc. No
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TL48643
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Call number
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1766575451; 10012825
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Main Entry
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Arab, Pezhman
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Title & Author
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Comparing three estimation methods for the three-parameter logistic IRT model\ Sunil LamsalSheng, Yanyan
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College
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Southern Illinois University at Carbondale
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Date
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2015
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Degree
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Ph.D.
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field of study
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Quantitative Methods
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student score
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2015
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Page No
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130
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Note
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Committee members: Asner-Self, Kimberly; Bhattacharya, Bhaskar; Headrick, Todd C.; Koran, Jennifer
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Note
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Place of publication: United States, Ann Arbor; ISBN=978-1-339-47771-8
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Abstract
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Different estimation procedures have been developed for the unidimensional three?parameter item response theory (IRT) model. These techniques include the marginal maximum likelihood estimation, the fully Bayesian estimation using Markov chain Monte Carlo simulation techniques, and the Metropolis-Hastings Robbin-Monro estimation. With each technique, a prior can be specified to reflect prior belief on each model parameter. Previous studies evaluating the fully Bayesian estimation procedure for this model suggests that the model can be viewed as a mixture model, and it suffers from a non-convergence problem unless strong informative priors are specified for the item slope and intercept parameters. This study focused on comparing the three estimation methods for the three-parameter logistic (3PL) model in parameter estimation using Monte Carlo simulations. In particular, sample sizes, test lengths, prior specifications and actual item parameters were manipulated to reflect various test situations. The results suggest that: 1) all three estimation methods performed differently under different simulation conditions, 2) the three methods performed better when the actual parameters are close to their prior mean or mode than when the actual parameters are close to their boundary values, 3) a relatively more informative prior had to be specified for item parameters to ensure convergence with each of the three methods and the item parameters were more accurately estimated.
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Subject
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Educational tests measurements
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Descriptor
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Education;Educational testing;Item response theory
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Added Entry
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Sheng, Yanyan
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Added Entry
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Quantitative MethodsSouthern Illinois University at Carbondale
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