Diagnostic classification models (DCMs) are psychometric models that can be used to estimate the presence or absence of psychological traits, or proficiency on fine-grained skills. Critical to the use of any psychometric model in practice, including DCMs, is an evaluation of model fit. Traditionally, DCMs have been estimated with maximum…

Testing organizations are faced with increasing demand to provide subscores in addition to the total test score. However, psychometricians argue that most subscores do not have added value to be worth reporting. To have added value, subscores need to meet a number of criteria: they should be reliable, distinctive, and distinct from each other and…

Background: Modelling academic self-concept through second-order factors or bifactor structures is an important issue with substantive and practical implications; besides, the bifactor model has not been analysed with a Chinese sample and cross-cultural studies in the academic self-concept are scarce. Likewise, latent structure validity evidence…

Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…

In Germany enrolment in majors is of considerable interest to academic departments, because their budget depends on the number of enrolled students. Besides observed factors, we presume that unobserved latent variables influence the major-choice decision of students. Using stated preferences data from a discrete choice experiment among students…

This article critically reviews how diagnostic models have been conceptualized and how they compare to other approaches used in educational measurement. In particular, certain assumptions that have been taken for granted and used as defining characteristics of diagnostic models are reviewed and it is questioned whether these assumptions are the…

This study explores the psychometric properties of "Self-Determination Inventory: Student Report" (SDI:SR) in students with intellectual and developmental disabilities (IDD) and without disabilities in China. The paper-and-pencil version of SDI:SR Chinese Translation (SDI:SR Chinese) was used to explore self-determination across students…

Recent advances have enabled diagnostic classification models (DCMs) to accommodate longitudinal data. These longitudinal DCMs were developed to study how examinees change, or transition, between different attribute mastery statuses over time. This study examines using longitudinal DCMs as an approach to assessing growth and serves three purposes:…

International large-scale assessments (ILSAs) transitioned from paper-based assessments to computer-based assessments (CBAs) facilitating the use of new item types and more effective data collection tools. This allows implementation of more complex test designs and to collect process and response time (RT) data. These new data types can be used to…

The study proposes a multicomponent model of subjective well-being (SWB) in elementary school. The model includes satisfaction with school, affect toward school, well-being related to communication with peers, and subjective physical well-being. The aim of this study is to verify whether well-being related to different aspects of school life can…

Assessing job applicants' general mental ability online poses psychometric challenges due to the necessity of having brief but accurate tests. Recent research (Myszkowski & Storme, 2018) suggests that recovering distractor information through Nested Logit Models (NLM; Suh & Bolt, 2010) increases the reliability of ability estimates in…

Valid indigenous language assessments are needed to further our understanding of how children learn language around the world. We assessed the psychometric properties and performance of two caregiver-report measures of Wolof language skill (language milestones achieved and vocabulary knowledge) for 500 children (ages 0;4 to 2;6) living in rural…

The objective of this research was to determine the effect of absenteeism and presenteeism on the academic performance of undergraduate students from the Business and Engineering Schools in Peruvian Universities. The study is based on a self-report survey of 8,203 students from the business and engineering schools of Peruvian universities. Scales…

This study compares the performance of two estimation algorithms of new usage, the Metropolis-Hastings Robins-Monro (MHRM) and the Hamiltonian MCMC (HMC), with two consolidated algorithms in the psychometric literature, the marginal likelihood via EM algorithm (MML-EM) and the Markov chain Monte Carlo (MCMC), in the estimation of multidimensional…

General diagnostic models (GDMs) and Bayesian networks are mathematical frameworks that cover a wide variety of psychometric models. Both extend latent class models, and while GDMs also extend item response theory (IRT) models, Bayesian networks can be parameterized using discretized IRT. The purpose of this study is to examine similarities and…