@article {379,
	title = {Small sample estimation in dichotomous item response models: Effect of priors based on judgmental information on the accuracy of item parameter estimates},
	journal = {Applied Psychological Measurement},
	volume = {27},
	number = {1},
	year = {2003},
	note = {Sage Publications, US},
	pages = {27-51},
	abstract = {Large item banks with properly calibrated test items are essential for ensuring the validity of computer-based tests. At the same time, item calibrations with small samples are desirable to minimize the amount of pretesting and limit item exposure. Bayesian estimation procedures show considerable promise with small examinee samples. The purposes of the study were (a) to examine how prior information for Bayesian item parameter estimation can be specified and (b) to investigate the relationship between sample size and the specification of prior information on the accuracy of item parameter estimates. The results of the simulation study were clear: Estimation of item response theory (IRT) model item parameters can be improved considerably. Improvements in the one-parameter model were modest; considerable improvements with the two- and three-parameter models were observed. Both the study of different forms of priors and ways to improve the judgmental data used in forming the priors appear to be promising directions for future research. },
	author = {Swaminathan, H. and Hambleton, R. K. and Sireci, S. G. and Xing, D. and Rizavi, S. M.}
}
@conference {1121,
	title = {The effect of test and examinee characteristics on the occurrence of aberrant response patterns in a computerized adaptive test},
	booktitle = {Paper presented at the annual meeting of the American Educational Research Association},
	year = {2001},
	note = {$\#$RI01-01},
	address = {Seattle WA},
	author = {Rizavi, S. and Swaminathan, H.}
}
