Rasch common-item equating is often used in high-stakes testing to maintain equivalent passing standards across test administrations. If unaddressed, item parameter drift poses a major threat to the accuracy of Rasch common-item equating. We compared the performance of well-established and newly developed drift detection methods in small and large…

The present study aims to examine gender differential item functioning (DIF) in the reading comprehension section of a high stakes test using cognitive diagnosis models. Based on the multiple-group generalized deterministic, noisy "and" gate (MG G-DINA) model, the Wald test and likelihood ratio test are used to detect DIF. The flagged…

Mixture IRT models address the heterogeneity in a population by extracting latent classes and allowing item parameters to vary between latent classes. Once the latent classes are extracted, they need to be further examined to be characterized. Some approaches have been adopted in the literature for this purpose. These approaches examine either the…

We used simulation techniques to assess the item-level and familywise Type I error control and power of an IRT item-fit statistic, the "S-X"[superscript 2]. Previous research indicated that the "S-X"[superscript 2] has good Type I error control and decent power, but no previous research examined familywise Type I error control.…

The purpose of this study is to address the necessity of subscore equating and to evaluate the performance of various equating methods for subtests. Assuming the random groups design and number-correct scoring, this paper analyzed real data and simulated data with four study factors including test dimensionality, subtest length, form difference in…

In applications of item response theory (IRT), fixed parameter calibration (FPC) has been used to estimate the item parameters of a new test form on the existing ability scale of an item pool. The present paper presents an application of FPC to multiple examinee groups test data that are linked to the item pool via anchor items, and investigates…

This study examined the effect of similar vs. dissimilar proficiency distributions on uniform DIF detection on a statewide eighth grade mathematics assessment. Results from the similar- and dissimilar-ability reference groups with an SWD focal group were compared for four models: logistic regression, hierarchical generalized linear model (HGLM),…

The literature on Automated Essay Scoring (AES) systems has provided useful validation frameworks for any assessment that includes AES scoring. Furthermore, evidence for the scoring fidelity of AES systems is accumulating. Yet questions remain when appraising the scoring performance of AES systems. These questions include: (a) which essays are…

In the current study, two pools of 250 essays, all written as a response to the same prompt, were rated by two groups of raters (14 or 15 raters per group), thereby providing an approximation to the essay's true score. An automated essay scoring (AES) system was trained on the datasets and then scored the essays using a cross-validation scheme. By…

Automated scoring systems are typically evaluated by comparing the performance of a single automated rater item-by-item to human raters. This presents a challenge when the performance of multiple raters needs to be compared across multiple items. Rankings could depend on specifics of the ranking procedure; observed differences could be due to…

In applications of item response theory (IRT) models, it is known that empirical violations of the local independence (LI) assumption can significantly bias parameter estimates. To address this issue, we propose a threshold-autoregressive item response theory (TAR-IRT) model that additionally accounts for order dependence among the item responses…

Item response time data were used in investigating the differences in student test-taking behavior between two device conditions: computer and tablet. Analyses were conducted to address the questions of whether or not the device condition had a differential impact on rapid guessing and solution behaviors (with response time effort used as an…

The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…

This article presents a new perspective on measuring gender differences in the large-scale assessment study Trends in International Science Study (TIMSS). The suggested empirical model is directly based on the theoretical competence model of the domain mathematics and thus includes the interaction between content and cognitive sub-competencies.…

It has long been argued that U.S. states' differential performance on nationwide assessments may reflect differences in students' opportunity to learn the tested content that is primarily due to variation in curricular content standards, rather than in instructional quality or educational investment. To quantify the effect of differences in…