Forced-choice (FC) measures have been widely used in many personality or attitude tests as an alternative to rating scales, which employ comparative rather than absolute judgments. Several response biases, such as social desirability, response styles, and acquiescence bias, can be reduced effectively. Another type of data linked with comparative…

The cross-classified data structure is ubiquitous in education, psychology, and health outcome sciences. In these areas, assessment instruments that are made up of multiple items are frequently used to measure latent constructs. The presence of both the cross-classified structure and multivariate categorical outcomes leads to the so-called…

Evaluating scale comparability in international large-scale assessments depends on measurement invariance (MI). The root mean square deviation (RMSD) is a standard method for establishing MI in several programs, such as the Programme for International Student Assessment and the Programme for the International Assessment of Adult Competencies.…

Classroom observational protocols, in which raters observe and score the quality of teachers' instructional practices, are often used to evaluate teachers for consequential purposes despite evidence that scores from such protocols are frequently driven by factors, such as rater and temporal effects, that have little to do with teacher quality. In…

Common indicator-based approaches to identifying careless and insufficient effort responding (C/IER) in survey data scan response vectors or timing data for aberrances, such as patterns signaling straight lining, multivariate outliers, or signals that respondents rushed through the administered items. Each of these approaches is susceptible to…

Teachers need instructionally useful data to make timely and appropriate decisions to meet their students with intensive needs (Filderman et al., 2019). Teachers have still experienced difficulty in instructional decision making in response to students' CBM data (Gesel et al., 2021). This is because data itself that was used for simply determining…

The study describes the development and preliminary psychometric validation of the Suicidal Ideation Attributes Scale-Modified (SIDAS-M), a five-item assessment of suicidal ideation for use with autistic adults. Participants (n = 102 autistic adults; 58% women, 34% men, 8% nonbinary; M[subscript age] = 41.75, SD = 12.89) completed an online survey…

In the literature of modern psychometric modeling, mostly related to item response theory (IRT), the fit of model is evaluated through known indices, such as X[superscript 2], M2, and root mean square error of approximation (RMSEA) for absolute assessments as well as Akaike information criterion (AIC), consistent AIC (CAIC), and Bayesian…

This article presents generalizations of SIBTEST and crossing-SIBTEST statistics for differential item functioning (DIF) investigations involving more than two groups. After reviewing the original two-group setup for these statistics, a set of multigroup generalizations that support contrast matrices for joint tests of DIF are presented. To…

Modeling, responding, and instructing have all been investigated as ways in which adults promote children's emotional competence, but they have largely been investigated separately. To facilitate the development of effective professional development models which promote teachers' engagement in emotion-focused teaching, it is important to…

Estimating reliability for single-item motivational measures presents challenges, particularly when constructs are anticipated to vary across time (e.g., effort, self-efficacy, emotions). We explored an innovative approach for estimating reliability of single-item motivational measures by defining reliability as consistency of interpreting the…

Screening items for parameter drift helps protect against serious validity threats and ensure score comparability when equating forms. Although many high-stakes credentialing examinations operate with small sample sizes, few studies have investigated methods to detect drift in small sample equating. This study demonstrates that several newly…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

Mixed Membership Models (MMMs) are a popular family of latent structure models for complex multivariate data. Instead of forcing each subject to belong to a single cluster, MMMs incorporate a vector of subject-specific weights characterizing partial membership across clusters. With this flexibility come challenges in uniquely identifying,…