@article {77,
	title = {The maximum priority index method for severely constrained item selection in computerized adaptive testing},
	journal = {British Journal of Mathematical and Statistical Psychology},
	volume = {62},
	number = {2},
	year = {2009},
	note = {Cheng, YingChang, Hua-HuaResearch Support, Non-U.S. Gov{\textquoteright}tEnglandThe British journal of mathematical and statistical psychologyBr J Math Stat Psychol. 2009 May;62(Pt 2):369-83. Epub 2008 Jun 2.},
	month = {May},
	pages = {369-83},
	edition = {2008/06/07},
	abstract = {This paper introduces a new heuristic approach, the maximum priority index (MPI) method, for severely constrained item selection in computerized adaptive testing. Our simulation study shows that it is able to accommodate various non-statistical constraints simultaneously, such as content balancing, exposure control, answer key balancing, and so on. Compared with the weighted deviation modelling method, it leads to fewer constraint violations and better exposure control while maintaining the same level of measurement precision.},
	keywords = {Aptitude Tests/*statistics \& numerical data, Diagnosis, Computer-Assisted/*statistics \& numerical data, Educational Measurement/*statistics \& numerical data, Humans, Mathematical Computing, Models, Statistical, Personality Tests/*statistics \& numerical data, Psychometrics/*statistics \& numerical data, Reproducibility of Results, Software},
	isbn = {0007-1102 (Print)0007-1102 (Linking)},
	author = {Cheng, Y and Chang, Hua-Hua}
}
@article {188,
	title = {Item selection in computerized adaptive testing: Should more discriminating items be used first?},
	journal = {Journal of Educational Measurement},
	volume = {38},
	number = {3},
	year = {2001},
	pages = {249-266},
	abstract = {During computerized adaptive testing (CAT), items are selected continuously according to the test-taker{\textquoteright}s estimated ability. Test security has become a problem because high-discrimination items are more likely to be selected and become overexposed. So, there seems to be a tradeoff between high efficiency in ability estimations and balanced usage of items. This series of four studies addressed the dilemma by focusing on the notion of whether more or less discriminating items should be used first in CAT. The first study demonstrated that the common maximum information method with J. B. Sympson and R. D. Hetter (1985) control resulted in the use of more discriminating items first. The remaining studies showed that using items in the reverse order, as described in H. Chang and Z. Yings (1999) stratified method had potential advantages: (a) a more balanced item usage and (b) a relatively stable resultant item pool structure with easy and inexpensive management. This stratified method may have ability-estimation efficiency better than or close to that of other methods. It is argued that the judicious selection of items, as in the stratified method, is a more active control of item exposure. (PsycINFO Database Record (c) 2005 APA )},
	keywords = {ability, Adaptive Testing, Computer Assisted Testing, Estimation, Statistical, Test Items computerized adaptive testing},
	author = {Hau, Kit-Tai and Chang, Hua-Hua}
}
@article {70,
	title = {A comparison of item selection rules at the early stages of computerized adaptive testing},
	journal = {Applied Psychological Measurement},
	volume = {24},
	number = {3},
	year = {2000},
	pages = {241-255},
	abstract = {The effects of 5 item selection rules--Fisher information (FI), Fisher interval information (FII), Fisher information with a posterior distribution (FIP), Kullback-Leibler information (KL), and Kullback-Leibler information with a posterior distribution (KLP)--were compared with respect to the efficiency and precision of trait (θ) estimation at the early stages of computerized adaptive testing (CAT). FII, FIP, KL, and KLP performed marginally better than FI at the early stages of CAT for θ=-3 and -2. For tests longer than 10 items, there appeared to be no precision advantage for any of the selection rules. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)},
	keywords = {Adaptive Testing, Computer Assisted Testing, Item Analysis (Test), Statistical Estimation computerized adaptive testing},
	author = {Chen, S-Y. and Ankenmann, R. D. and Chang, Hua-Hua}
}
