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Estimating Multidimensional Item Response Models With Mixed Structure ASSEST IRT

Zhang, Jinming
Publication Year:
Report Number:
ETS Research Report
Document Type:
Page Count:
Subject/Key Words:
Genetic Algorithm, Approximate Simple Structure ESTimation (ASSEST), Estimation (Mathematics), Item Response Theory (IRT), Multidimensional Item Response Theory (MIRT), Mixed Structure, Approximate Simple Structure


This study derived an expectation-maximization (EM) algorithm for estimating the parameters of multidimensional item response models. A genetic algorithm (GA) was developed to be used in the maximization step in each EM cycle. The focus of the EM-GA algorithm developed in this paper was on multidimensional items with mixed structure. Simulated item response data were generated and then estimated by a computer program based on the EM-GA algorithm. The simulation results demonstrate that the EM-GA algorithm is a very promising approach in estimating multidimensional item response model parameters.

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