ERIC Number: EJ1238356
Record Type: Journal
Publication Date: 2019-Dec
Pages: 16
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-2330-8516
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Available Date: N/A
Maximum Marginal Likelihood Estimation with an Expectation-Maximization Algorithm for Multigroup/Mixture Multidimensional Item Response Theory Models. Research Report. ETS RR-19-35
Fu, Jianbin
ETS Research Report Series, Dec 2019
A maximum marginal likelihood estimation with an expectation-maximization algorithm has been developed for estimating multigroup or mixture multidimensional item response theory models using the generalized partial credit function, graded response function, and 3-parameter logistic function. The procedure includes the estimation of item parameters, attribute population distribution parameters, and test takers' attributes. All estimation functions and derivatives are provided. This procedure has been implemented in an R program. A simulation study has been conducted using this R program on various models related to the generalized partial credit function, and the result shows reasonable parameter recovery.
Descriptors: Maximum Likelihood Statistics, Mathematics, Item Response Theory, Expectation, Simulation, Computation, Accuracy, Equations (Mathematics)
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
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Language: English
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