@article {2695,
	title = {Measurement Efficiency for Fixed-Precision Multidimensional Computerized Adaptive Tests: Comparing Health Measurement and Educational Testing Using Example Banks},
	journal = {Applied Psychological Measurement},
	volume = {43},
	number = {1},
	year = {2019},
	pages = {68-83},
	abstract = {It is currently not entirely clear to what degree the research on multidimensional computerized adaptive testing (CAT) conducted in the field of educational testing can be generalized to fields such as health assessment, where CAT design factors differ considerably from those typically used in educational testing. In this study, the impact of a number of important design factors on CAT performance is systematically evaluated, using realistic example item banks for two main scenarios: health assessment (polytomous items, small to medium item bank sizes, high discrimination parameters) and educational testing (dichotomous items, large item banks, small- to medium-sized discrimination parameters). Measurement efficiency is evaluated for both between-item multidimensional CATs and separate unidimensional CATs for each latent dimension. In this study, we focus on fixed-precision (variable-length) CATs because it is both feasible and desirable in health settings, but so far most research regarding CAT has focused on fixed-length testing. This study shows that the benefits associated with fixed-precision multidimensional CAT hold under a wide variety of circumstances.},
	doi = {10.1177/0146621618765719},
	url = {https://doi.org/10.1177/0146621618765719},
	author = {Muirne C. S. Paap and Sebastian Born and Johan Braeken}
}
@article {2519,
	title = {Heuristic Constraint Management Methods in Multidimensional Adaptive Testing},
	journal = {Educational and Psychological Measurement},
	volume = {77},
	number = {2},
	year = {2017},
	pages = {241-262},
	abstract = {Although multidimensional adaptive testing (MAT) has been proven to be highly advantageous with regard to measurement efficiency when several highly correlated dimensions are measured, there are few operational assessments that use MAT. This may be due to issues of constraint management, which is more complex in MAT than it is in unidimensional adaptive testing. Very few studies have examined the performance of existing constraint management methods (CMMs) in MAT. The present article focuses on the effectiveness of two promising heuristic CMMs in MAT for varying levels of imposed constraints and for various correlations between the measured dimensions. Through a simulation study, the multidimensional maximum priority index (MMPI) and multidimensional weighted penalty model (MWPM), as an extension of the weighted penalty model, are examined with regard to measurement precision and constraint violations. The results show that both CMMs are capable of addressing complex constraints in MAT. However, measurement precision losses were found to differ between the MMPI and MWPM. While the MMPI appears to be more suitable for use in assessment situations involving few to a moderate number of constraints, the MWPM should be used when numerous constraints are involved.},
	doi = {10.1177/0013164416643744},
	url = {http://dx.doi.org/10.1177/0013164416643744},
	author = {Sebastian Born and Andreas Frey}
}
