The assessment of model fit in latent trait modeling is an integral part of correctly applying the model. Still the assessment of model fit has been less utilized for ideal point models such as the Generalized Graded Unfolding Models (GGUM). The current study assesses the performance of the relative fit indices "AIC" and "BIC,"…

This article provides a process to carefully evaluate the suitability of a content domain for which diagnostic classification models (DCMs) could be applicable and then optimized steps for constructing a test blueprint for applying DCMs and a real-life example illustrating this process. The content domains were carefully evaluated using a set of…

Objectively scoring constructed-response items on educational assessments has long been a challenge due to the use of human raters. Even well-trained raters using a rubric can inaccurately assess essays. Unfolding models measure rater's scoring accuracy by capturing the discrepancy between criterion and operational ratings by placing essays on an…

Most methods for structural equation modeling (SEM) focused on the analysis of covariance matrices. However, "Historically, interesting psychological theories have been phrased in terms of correlation coefficients." This might be because data in social and behavioral sciences typically do not have predefined metrics. While proper methods…

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…

This study aimed to examine authentic models of science assessment in assessing the competence of senior high school students who met the criteria of validity, practicality, and effectiveness. The methodology applied was an evaluation and developmental research. Research was conducted in senior high school in accordance with the needs of the…

This dissertation aims to investigate the effect size measures of differential item functioning (DIF) detection in the context of cognitive diagnostic models (CDMs). A variety of DIF detection techniques have been developed in the context of CDMs. However, most of the DIF detection procedures focus on the null hypothesis significance test. Few…

The application of diagnostic classification models (DCMs) in the field of educational measurement is getting more attention in recent years. To make a valid inference from the model, it is important to ensure that the model fits the data. The purpose of the present study was to investigate the performance of the limited information…

The nonequivalent groups with anchor test (NEAT) design is widely used in test equating. Under this design, two groups of examinees are administered different test forms with each test form containing a subset of common items. Because test takers from different groups are assigned only one test form, missing score data emerge by design rendering…

The use of unidimensional scales that contain both positively and negatively worded items is common in both the educational and psychological fields. However, dimensionality investigations of these instruments often lead to a rejection of the theorized unidimensional model in favor of multidimensional structures, leaving researchers at odds for…

S-X[superscript 2] is a popular item fit index that is available in commercial software packages such as "flex"MIRT. However, no research has systematically examined the performance of S-X[superscript 2] for detecting item misfit within the context of the multidimensional graded response model (MGRM). The primary goal of this study was…

The semi-generalized partial credit model (Semi-GPCM) has been proposed as a unidimensional modeling method for handling not applicable scale responses and neutral scale responses, and it has been suggested that the model may be of use in handling missing data in scale items. The purpose of this study is to evaluate the ability of the…

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…

This simulation study examines the characteristics of the Explanatory Item Response Model (EIRM) when estimating treatment effects when compared to classical test theory (CTT) sum and mean scores and item response theory (IRT)-based theta scores. Results show that the EIRM and IRT theta scores provide generally equivalent bias and false positive…

This paper examines the scalability of the results from the Tennessee Student-Teacher Achievement Ratio (STAR) Project, a prominent educational experiment. We explore how the misalignment between the experimental design and the econometric model affects researchers' ability to learn about the intervention's scalability. We document heterogeneity…