@article {2250,
	title = {Computerized Adaptive Testing Using a Class of High-Order Item Response Theory Models},
	journal = {Applied Psychological Measurement},
	volume = {36},
	number = {8},
	year = {2012},
	pages = {689-706},
	abstract = {<p>In the human sciences, a common assumption is that latent traits have a hierarchical structure. Higher order item response theory models have been developed to account for this hierarchy. In this study, computerized adaptive testing (CAT) algorithms based on these kinds of models were implemented, and their performance under a variety of situations was examined using simulations. The results showed that the CAT algorithms were very effective. The progressive method for item selection, the Sympson and Hetter method with online and freeze procedure for item exposure control, and the multinomial model for content balancing can simultaneously maintain good measurement precision, item exposure control, content balance, test security, and pool usage.</p>
},
	doi = {10.1177/0146621612459552},
	url = {http://apm.sagepub.com/content/36/8/689.abstract},
	author = {Huang, Hung-Yu and Chen, Po-Hsi and Wang, Wen-Chung}
}
@article {2136,
	title = {Implementation and Measurement Efficiency of Multidimensional Computerized Adaptive Testing},
	journal = {Applied Psychological Measurement},
	volume = {28},
	number = {5},
	year = {2004},
	pages = {295-316},
	abstract = {<p>Multidimensional adaptive testing (MAT) procedures are proposed for the measurement of several latent traits by a single examination. Bayesian latent trait estimation and adaptive item selection are derived. Simulations were conducted to compare the measurement efficiency of MAT with those of unidimensional adaptive testing and random administration. The results showed that the higher the correlation between latent traits, the more latent traits there were, and the more scoring levels there were in the items, the more efficient MAT was than the other two procedures. For tests containing multidimensional items, only MAT is applicable, whereas unidimensional adaptive testing is not. Issues in implementing MAT are discussed.</p>
},
	doi = {10.1177/0146621604265938},
	url = {http://apm.sagepub.com/content/28/5/295.abstract},
	author = {Wang, Wen-Chung and Chen, Po-Hsi}
}
