Insufficient effort responding (IER) refers to a lack of effort when answering survey or questionnaire items. Such items typically offer more than two ordered response categories, with Likert-type scales as the most prominent example. The underlying assumption is that the successive categories reflect increasing levels of the latent variable…

In many large-scale testing programs, examinees are frequently categorized into different performance levels. These classifications are then used to make high-stakes decisions about examinees in contexts such as in licensure, certification, and educational assessments. Numerous approaches to estimating the consistency and accuracy of this…

Some previous studies suggest that response times (RTs) on rating scale items can be informative about the content trait, but a more recent study suggests they may also be reflective of response styles. The latter result raises questions about the possible consideration of RTs for content trait estimation, as response styles are generally viewed…

A Q-matrix is a binary matrix that defines the relationship between items and latent variables and is widely used in diagnostic classification models (DCMs), and can also be adopted in multidimensional item response theory (MIRT) models. The construction process of the Q-matrix is typically carried out by experts in the subject area of the items…

A Q-matrix is a binary matrix that defines the relationship between items and latent variables and is widely used in diagnostic classification models (DCMs), and can also be adopted in multidimensional item response theory (MIRT) models. The construction process of the Q-matrix is typically carried out by experts in the subject area of the items…

In the existing multidimensional extensions of the log-normal response time (LNRT) model, the log response times are decomposed into a linear combination of several latent traits. These models are fully compensatory as low levels on traits can be counterbalanced by high levels on other traits. We propose an alternative multidimensional extension…

Economic efficiency demands accurate assessment of individual ability for selection purposes. This study investigates Classical Test Theory (CTT) and Item Response Theory (IRT) for estimating true ability and ranking individuals. Two Monte Carlo simulations and real data analyses were conducted. Results suggest a slight advantage for IRT, but…

Accurate item parameters and standard errors (SEs) are crucial for many multidimensional item response theory (MIRT) applications. A recent study proposed the Gaussian Variational Expectation Maximization (GVEM) algorithm to improve computational efficiency and estimation accuracy (Cho et al., 2021). However, the SE estimation procedure has yet to…

This article focuses on rater severity and consistency and their relation to major changes in the rating system in a high-stakes testing context. The study is based on longitudinal data collected from 2009 to 2019 from the second language (L2) Finnish speaking subtest in the National Certificates of Language Proficiency in Finland. We investigated…

Background: School feeding programs' evaluation requires the measurement of food insecurity, a more objective indicator, within school in low-income countries. The Global Child Nutrition Foundation (GCNF) uses subjective indicators to report school feeding coverage rates across many countries that participate in the global survey of school meal…

In this study, we administered and evaluated circular motion concept question items with a view to developing an inventory suitable for the Ugandan context. Before administering the circular concept items, six physics experts and ten undergraduate physics students carried out the face and content validation. One hundred eighteen undergraduate…

Item response theory (IRT) models typically rely on a normality assumption for subject-specific latent traits, which is often unrealistic in practice. Semiparametric extensions based on Dirichlet process mixtures (DPMs) offer a more flexible representation of the unknown distribution of the latent trait. However, the use of such models in the IRT…

Psychometricians have devoted much research and attention to categorical item responses, leading to the development and widespread use of item response theory for the estimation of model parameters and identification of items that do not perform in the same way for examinees from different population subgroups (e.g., differential item functioning…

Item response theory was used to study the psychometric properties of the Client Meaningful Experiences Scale (CMES). In a sample of 306 adult counseling clients, we examined the dimensional structure of the scale, item-fit, and person-fit statistics. Implications of these findings for counselors, counselors-in-training, and counseling researchers…

Several marginal effect size (ES) statistics suitable for quantifying the magnitude of differential item functioning (DIF) have been proposed in the area of item response theory; for instance, the Differential Functioning of Items and Tests (DFIT) statistics, signed and unsigned item difference in the sample statistics (SIDS, UIDS, NSIDS, and…