@article {96,
	title = {An examination of exposure control and content balancing restrictions on item selection in CATs using the partial credit model},
	journal = {Journal of Applied Measurement},
	volume = {4},
	number = {1},
	year = {2003},
	note = {1529-7713Journal Article},
	pages = {24-42},
	abstract = {The purpose of the present investigation was to systematically examine the effectiveness of the Sympson-Hetter technique and rotated content balancing relative to no exposure control and no content rotation conditions in a computerized adaptive testing system (CAT) based on the partial credit model. A series of simulated fixed and variable length CATs were run using two data sets generated to multiple content areas for three sizes of item pools. The 2 (exposure control) X 2 (content rotation) X 2 (test length) X 3 (item pool size) X 2 (data sets) yielded a total of 48 conditions. Results show that while both procedures can be used with no deleterious effect on measurement precision, the gains in exposure control, pool utilization, and item overlap appear quite modest. Difficulties involved with setting the exposure control parameters in small item pools make questionable the utility of the Sympson-Hetter technique with similar item pools.},
	keywords = {*Computers, *Educational Measurement, *Models, Theoretical, Automation, Decision Making, Humans, Reproducibility of Results},
	author = {Davis, L. L. and Pastor, D. A. and Dodd, B. G. and Chiang, C. and Fitzpatrick, S. J.}
}
@article {67,
	title = {The effect of population distribution and method of theta estimation on computerized adaptive testing (CAT) using the rating scale model},
	journal = {Educational \& Psychological Measurement},
	volume = {57},
	number = {3},
	year = {1997},
	note = {Sage Publications, US},
	pages = {422-439},
	abstract = {Investigated the effect of population distribution on maximum likelihood estimation (MLE) and expected a posteriori estimation (EAP) in a simulation study of computerized adaptive testing (CAT) based on D. Andrich{\textquoteright}s (1978) rating scale model. Comparisons were made among MLE and EAP with a normal prior distribution and EAP with a uniform prior distribution within 2 data sets: one generated using a normal trait distribution and the other using a negatively skewed trait distribution. Descriptive statistics, correlations, scattergrams, and accuracy indices were used to compare the different methods of trait estimation. The EAP estimation with a normal prior or uniform prior yielded results similar to those obtained with MLE, even though the prior did not match the underlying trait distribution. An additional simulation study based on real data suggested that more work is needed to determine the optimal number of quadrature points for EAP in CAT based on the rating scale model. The choice between MLE and EAP for particular measurement situations is discussed. (PsycINFO Database Record (c) 2003 APA, all rights reserved).},
	keywords = {computerized adaptive testing},
	author = {Chen, S-K. and Hou, L. Y. and Fitzpatrick, S. J. and Dodd, B. G.}
}
@article {501,
	title = {The effect of population distribution and methods of theta estimation on computerized adaptive testing (CAT) using the rating scale model},
	journal = {Educational and Psychological Measurement},
	volume = {57},
	year = {1997},
	pages = {422-439},
	author = {Chen, S. and Hou, L. and Fitzpatrick, S. J. and Dodd, B.}
}
@conference {952,
	title = {The effects of methods of theta estimation, prior distribution, and number of quadrature points on CAT using the graded response model},
	booktitle = {Paper presented at the annual meeting of the American Educational Research Association},
	year = {1996},
	address = {New York NY},
	author = {Hou, L. and Chen, S. and Dodd. B. G. and Fitzpatrick, S. J.}
}
@conference {882,
	title = {The effect of population distribution and methods of theta estimation on CAT using the rating scale model},
	booktitle = {Paper presented at the annual meeting of the American Educational Research Association},
	year = {1995},
	address = {San Francisco},
	author = {Chen, S. and Hou, L. and Fitzpatrick, S. J. and Dodd, B. G.}
}
