The purpose of this study was to investigate multidimensional DIF with a simple and nonsimple structure in the context of multidimensional Graded Response Model (MGRM). This study examined and compared the performance of the IRT-LR and Wald test using MML-EM and MHRM estimation approaches with different test factors and test structures in…

This study aims to analyze the differential bundle functioning in multidimensional tests with a specific purpose to detect this effect through differentiating the location of the item with DIF in the test, the correlation between the dimensions, the sample size, and the ratio of reference to focal group size. The first 10 items of the test that is…

In this article, we present a theory of test translation whose intent is to provide the conceptual foundation for effective, systematic work in the process of test translation and test translation review. According to the theory, translation error is multidimensional; it is not simply the consequence of defective translation but an inevitable fact…

This study linked nonlinear profile analysis (NPA) of dichotomous responses with an existing family of item response theory models and generalized latent variable models (GLVM). The NPA method offers several benefits over previous internal profile analysis methods: (a) NPA is estimated with maximum likelihood in a GLVM framework rather than…

In item response theory (IRT), preequating depends upon item parameter estimate invariance. Three separate simulations, all using the unidimensional three-parameter logistic item response model, were conducted to study the impact of the following variables on preequating: (1) mean differences in ability; (2) multidimensionality in the data; and…

In order to determine the effectiveness of multidimensional scaling (MDS) in recovering the dimensionality of a set of dichotomously-scored items, data were simulated in one, two, and three dimensions for a variety of correlations with the underlying latent trait. Similarity matrices were constructed from these data using three margin-sensitive…