@article {2728,
	title = {New Efficient and Practicable Adaptive Designs for Calibrating Items Online},
	journal = {Applied Psychological Measurement},
	volume = {44},
	number = {1},
	year = {2020},
	pages = {3-16},
	abstract = {When calibrating new items online, it is practicable to first compare all new items according to some criterion and then assign the most suitable one to the current examinee who reaches a seeding location. The modified D-optimal design proposed by van der Linden and Ren (denoted as D-VR design) works within this practicable framework with the aim of directly optimizing the estimation of item parameters. However, the optimal design point for a given new item should be obtained by comparing all examinees in a static examinee pool. Thus, D-VR design still has room for improvement in calibration efficiency from the view of traditional optimal design. To this end, this article incorporates the idea of traditional optimal design into D-VR design and proposes a new online calibration design criterion, namely, excellence degree (ED) criterion. Four different schemes are developed to measure the information provided by the current examinee when implementing this new criterion, and four new ED designs equipped with them are put forward accordingly. Simulation studies were conducted under a variety of conditions to compare the D-VR design and the four proposed ED designs in terms of calibration efficiency. Results showed that the four ED designs outperformed D-VR design in almost all simulation conditions.},
	doi = {10.1177/0146621618824854},
	url = {https://doi.org/10.1177/0146621618824854},
	author = {Yinhong He and Ping Chen and Yong Li}
}
