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Svetina, Dubravka; Levy, Roy – Journal of Experimental Education, 2016
This study investigated the effect of complex structure on dimensionality assessment in compensatory multidimensional item response models using DETECT- and NOHARM-based methods. The performance was evaluated via the accuracy of identifying the correct number of dimensions and the ability to accurately recover item groupings using a simple…
Descriptors: Item Response Theory, Accuracy, Correlation, Sample Size
Dirlik, Ezgi Mor – International Journal of Progressive Education, 2019
Item response theory (IRT) has so many advantages than its precedent Classical Test Theory (CTT) such as non-changing item parameters, ability parameter estimations free from the items. However, in order to get these advantages, some assumptions should be met and they are; unidimensionality, normality and local independence. However, it is not…
Descriptors: Comparative Analysis, Nonparametric Statistics, Item Response Theory, Models
Kalkan, Ömür Kaya; Kelecioglu, Hülya – Educational Sciences: Theory and Practice, 2016
Linear factor analysis models used to examine constructs underlying the responses are not very suitable for dichotomous or polytomous response formats. The associated problems cannot be eliminated by polychoric or tetrachoric correlations in place of the Pearson correlation. Therefore, we considered parameters obtained from the NOHARM and FACTOR…
Descriptors: Sample Size, Nonparametric Statistics, Factor Analysis, Correlation
Straat, J. Hendrik; van der Ark, L. Andries; Sijtsma, Klaas – Educational and Psychological Measurement, 2014
An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…
Descriptors: Sampling, Test Items, Effect Size, Scaling
Monahan, Patrick O.; Ankenmann, Robert D. – Applied Psychological Measurement, 2010
When the matching score is either less than perfectly reliable or not a sufficient statistic for determining latent proficiency in data conforming to item response theory (IRT) models, Type I error (TIE) inflation may occur for the Mantel-Haenszel (MH) procedure or any differential item functioning (DIF) procedure that matches on summed-item…
Descriptors: Error of Measurement, Item Response Theory, Test Bias, Scores
Alterman, Arthur I.; Cacciola, John S.; Habing, Brian; Lynch, Kevin G. – Psychological Assessment, 2007
Baseline Addiction Severity Index (5th ed.; ASI-5) data of 2,142 substance abuse patients were analyzed with two nonparametric item response theory (NIRT) methods: Mokken scaling and conditional covariance techniques. Nine reliable and dimensionally homogeneous Recent Problem indexes emerged in the ASI-5's seven areas, including two each in the…
Descriptors: Severity (of Disability), Psychometrics, Patients, Employment
A Comparative Study of Test Data Dimensionality Assessment Procedures Under Nonparametric IRT Models
van Abswoude, Alexandra A. H.; van der Ark, L. Andries; Sijtsma, Klaas – Applied Psychological Measurement, 2004
In this article, an overview of nonparametric item response theory methods for determining the dimensionality of item response data is provided. Four methods were considered: MSP, DETECT, HCA/CCPROX, and DIMTEST. First, the methods were compared theoretically. Second, a simulation study was done to compare the effectiveness of MSP, DETECT, and…
Descriptors: Comparative Analysis, Computer Software, Simulation, Nonparametric Statistics