@article {2754,
	title = {How Do Trait Change Patterns Affect the Performance of Adaptive Measurement of Change?},
	journal = {Journal of Computerized Adaptive Testing},
	volume = {10},
	year = {2023},
	pages = {32-58},
	keywords = {adaptive measurement of change, computerized adaptive testing, longitudinal measurement, trait change patterns},
	doi = {10.7333/2307-1003032},
	author = {Ming Him Tai and Allison W. Cooperman and Joseph N. DeWeese and David J. Weiss}
}
@article {2717,
	title = {Time-Efficient Adaptive Measurement of Change},
	journal = {Journal of Computerized Adaptive Testing},
	volume = {7},
	year = {2019},
	pages = {15-34},
	abstract = {<p>The adaptive measurement of change (AMC) refers to the use of computerized adaptive testing (CAT) at multiple occasions to efficiently assess a respondent\&rsquo;s improvement, decline, or sameness from occasion to occasion. Whereas previous AMC research focused on administering the most informative item to a respondent at each stage of testing, the current research proposes the use of Fisher information per time unit as an item selection procedure for AMC. The latter procedure incorporates not only the amount of information provided by a given item but also the expected amount of time required to complete it. In a simulation study, the use of Fisher information per time unit item selection resulted in a lower false positive rate in the majority of conditions studied, and a higher true positive rate in all conditions studied, compared to item selection via Fisher information without accounting for the expected time taken. Future directions of research are suggested.</p>
},
	keywords = {adaptive measurement of change, computerized adaptive testing, Fisher information, item selection, response-time modeling},
	issn = {2165-6592},
	doi = {10.7333/1909-0702015},
	url = {http://iacat.org/jcat/index.php/jcat/article/view/73/35},
	author = {Matthew Finkelman and Chun Wang}
}
