@article {74,
	title = {Estimation of trait level in computerized adaptive testing},
	journal = {Applied Psychological Measurement},
	volume = {24},
	number = {3},
	year = {2000},
	pages = {257-265},
	abstract = {Notes that in computerized adaptive testing (CAT), a examinee{\textquoteright}s trait level (θ) must be estimated with reasonable accuracy based on a small number of item responses. A successful implementation of CAT depends on (1) the accuracy of statistical methods used for estimating θ and (2) the efficiency of the item-selection criterion. Methods of estimating θ suitable for CAT are reviewed, and the differences between Fisher and Kullback-Leibler information criteria for selecting items are discussed. The accuracy of different CAT algorithms was examined in an empirical study. The results show that correcting θ estimates for bias was necessary at earlier stages of CAT, but most CAT algorithms performed equally well for tests of 10 or more items. (PsycINFO Database Record (c) 2005 APA )},
	keywords = {(Statistical), Adaptive Testing, Computer Assisted Testing, Item Analysis, Statistical Estimation computerized adaptive testing},
	author = {Cheng, P. E. and Liou, M.}
}
