@article {2690,
	title = {A Continuous a-Stratification Index for Item Exposure Control in Computerized Adaptive Testing},
	journal = {Applied Psychological Measurement},
	volume = {42},
	number = {7},
	year = {2018},
	pages = {523-537},
	abstract = {The method of a-stratification aims to reduce item overexposure in computerized adaptive testing, as items that are administered at very high rates may threaten the validity of test scores. In existing methods of a-stratification, the item bank is partitioned into a fixed number of nonoverlapping strata according to the items{\textquoteright}a, or discrimination, parameters. This article introduces a continuous a-stratification index which incorporates exposure control into the item selection index itself and thus eliminates the need for fixed discrete strata. The new continuous a-stratification index is compared with existing stratification methods via simulation studies in terms of ability estimation bias, mean squared error, and control of item exposure rates.},
	doi = {10.1177/0146621618758289},
	url = {https://doi.org/10.1177/0146621618758289},
	author = {Alan Huebner and Chun Wang and Bridget Daly and Colleen Pinkelman}
}
