This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…

Recent research has shown that over-extraction of latent classes can be observed in the Bayesian estimation of the mixed Rasch model when the distribution of ability is non-normal. This study examined the effect of non-normal ability distributions on the number of latent classes in the mixed Rasch model when estimated with maximum likelihood…

Raju, van der Linden, and Fleer (1995) introduced a framework for differential functioning of items and tests (DFIT) for unidimensional dichotomous models. Since then, DFIT has been shown to be a quite versatile framework as it can handle polytomous as well as multidimensional models both at the item and test levels. However, DFIT is still limited…

Cognitive ability tests are widely used in organizations around the world because they have high predictive validity in selection contexts. Although these tests typically measure several subdomains, testing is usually carried out for a single subdomain at a time. This can be ineffective when the subdomains assessed are highly correlated. This…

Test compromise is a concern in cognitive ability testing because such tests are widely used in employee selection and administered on a continuous basis. In this study, the resistance of cognitive tests, deployed in different test systems, to small-scale cheating conspiracies, was evaluated regarding the accuracy of ability estimation.…

Differential item functioning (DIF) analysis is a statistical technique used for ensuring the equity and fairness of educational assessments. This study formulates a new DIF analysis method using the information similarity index (ISI). ISI compares item information functions when data fits the Rasch model. Through simulations and an international…

The study of measurement models in psychometrics by means of dimensionality reduction techniques such as Principal Components Analysis (PCA) is a very common practice. In recent times, an upsurge of interest in the study of artificial neural networks apt to computing a principal component extraction has been observed. Despite this interest, the…

There has been considerable research regarding the extent to which psychometric sound assessments sometimes yield individual score estimates that are inconsistent with the response patterns of the individual. It has been suggested that individual response patterns may differ from expectations for a number of reasons, including subject motivation,…