Abstract
Advanced Item Response Theory (IRT) practices serve well in understanding the nature of latent variables which have been subject to research in various disciplines. In the current study, 7-12 aged 2536 children’s responses to 20-item Visual Sequential Processing Memory (VSPM) sub-test of Anadolu-Sak Intelligence Scale (ASIS) were analyzed with Mixture Rasch Method (MRM). In the first phase of the study, concomitant (covariate) variables were not used. In the second phase, age and gender were added to the model, and then the two models were compared in terms of fit indices, the number of latent classes and the distribution of item difficulties in the latent classes. The results of the study suggested that there were three latent classes in both models; however, the latter model had greater fit compared to the former model. In addition, the latent classes in both models had similar characteristics, and the distributions of item difficulties in latent classes were also quite similar in both models while they had some differences in some aspects. The sizes of identical latent classes in both models varied between 15% and 30%. The results of the current study are expected to provide a deeper insight to researchers studying measurement theory and/or intelligence measurement.
Highlights
New methods in measurement theory have a pivotal role in understanding the nature of latent variables which have been subject to research in various disciplines
Since the lowest Bayesian Information Criterion (BIC) value was obtained for three-class solution, it was decided that the optimum latent class number for the data set was three
The results of the current study indicate that the classes were formed in line with Visual Sequential Processing Memory (VSPM) levels in a similar way with the first model
Summary
New methods in measurement theory have a pivotal role in understanding the nature of latent variables which have been subject to research in various disciplines. In parallel with this view, new methods in measurement theory have been used in the measurement of intelligence which has a background of more than a century. That a population consists of homogenous unknown sub-groups is a manifestation of this limitation (von Davier & Rost, 2017). This paves the way for new practices in IRT
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