Testlets bring several perks in the development and administration of tests, such as 1) the construction of meaningful test items, 2) the avoidance of non-relevant context exposure, 3) the improvement of testing efficiency, and 4) the progression of testlet items requiring higher thinking skills. Thus, the inclusion of testlets in educational…

The present study investigates different approaches to adding covariates and the impact in fitting mixture item response theory models. Mixture item response theory models serve as an important methodology for tackling several psychometric issues in test development, including the detection of latent differential item functioning. A Monte Carlo…

Rasch and classical test analysis methods were compared with respect to their similarities and differences in the identification of noninformative items and implausible person records. Using computer simulated data with known parameters, each model was evaluated in terms of its effectiveness in: (1) identifying noninformative or "bad"…

This Monte Carlo study examined the effect of complex sampling of items on the measurement of differential item functioning (DIF) using the Mantel-Haenszel procedure. Data were generated using a three-parameter logistic item response theory model according to the balanced incomplete block (BIB) design used in the National Assessment of Educational…

Multidimensional item response theory (IRT) models have been proposed for better understanding the dimensional structure of data or to define diagnostic profiles of student learning. A compensatory multidimensional two-parameter partial credit model (M-2PPC) for constructed-response items is presented that is a generalization of those proposed to…