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Stephen L. Wright; Michael A. Jenkins-Guarnieri – Journal of Psychoeducational Assessment, 2024
The current study sought out to advance the Social Self-Efficacy and Social Outcome Expectations scale using multiple approaches to scale development. Data from 583 undergraduate students were used in two scale development approaches: Classic Test Theory (CTT) and Item Response Theory (IRT). Confirmatory factor analysis suggested a 2-factor…
Descriptors: Measures (Individuals), Expectation, Self Efficacy, Item Response Theory
Ryan M. Cook; Stefanie A. Wind – Measurement and Evaluation in Counseling and Development, 2024
The purpose of this article is to discuss reliability and precision through the lens of a modern measurement approach, item response theory (IRT). Reliability evidence in the field of counseling is primarily generated using Classical Test Theory (CTT) approaches, although recent studies in the field of counseling have shown the benefits of using…
Descriptors: Item Response Theory, Measurement, Reliability, Accuracy
Seyma Erbay Mermer – Pegem Journal of Education and Instruction, 2024
This study aims to compare item and student parameters of dichotomously scored multidimensional constructs estimated based on unidimensional and multidimensional Item Response Theory (IRT) under different conditions of sample size, interdimensional correlation and number of dimensions. This research, conducted with simulations, is of a basic…
Descriptors: Item Response Theory, Correlation, Error of Measurement, Comparative Analysis
Dubravka Svetina Valdivia; Shenghai Dai – Journal of Experimental Education, 2024
Applications of polytomous IRT models in applied fields (e.g., health, education, psychology) are abound. However, little is known about the impact of the number of categories and sample size requirements for precise parameter recovery. In a simulation study, we investigated the impact of the number of response categories and required sample size…
Descriptors: Item Response Theory, Sample Size, Models, Classification
Jiangqiong Li – ProQuest LLC, 2024
When measuring latent constructs, for example, language ability, we use statistical models to specify appropriate relationships between the latent construct and observe responses to test items. These models rely on theoretical assumptions to ensure accurate parameter estimates for valid inferences based on the test results. This dissertation…
Descriptors: Goodness of Fit, Item Response Theory, Models, Measurement Techniques
Franz Classe; Christoph Kern – Educational and Psychological Measurement, 2024
We develop a "latent variable forest" (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on "confirmatory factor analysis" (CFA) models with ordinal and/or numerical response variables. Through parametric model…
Descriptors: Algorithms, Item Response Theory, Artificial Intelligence, Factor Analysis
Zsuzsa Bakk – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A standard assumption of latent class (LC) analysis is conditional independence, that is the items of the LC are independent of the covariates given the LCs. Several approaches have been proposed for identifying violations of this assumption. The recently proposed likelihood ratio approach is compared to residual statistics (bivariate residuals…
Descriptors: Goodness of Fit, Error of Measurement, Comparative Analysis, Models
Chunyan Liu; Raja Subhiyah; Richard A. Feinberg – Applied Measurement in Education, 2024
Mixed-format tests that include both multiple-choice (MC) and constructed-response (CR) items have become widely used in many large-scale assessments. When an item response theory (IRT) model is used to score a mixed-format test, the unidimensionality assumption may be violated if the CR items measure a different construct from that measured by MC…
Descriptors: Test Format, Response Style (Tests), Multiple Choice Tests, Item Response Theory
Joakim Wallmark; James O. Ramsay; Juan Li; Marie Wiberg – Journal of Educational and Behavioral Statistics, 2024
Item response theory (IRT) models the relationship between the possible scores on a test item against a test taker's attainment of the latent trait that the item is intended to measure. In this study, we compare two models for tests with polytomously scored items: the optimal scoring (OS) model, a nonparametric IRT model based on the principles of…
Descriptors: Item Response Theory, Test Items, Models, Scoring
Quan Hoang Nguyen Tran – SAGE Open, 2024
The influence of Michigan leadership behaviors in organizational variables has been conducted in the Western context. However, limited studies have been conducted in the Vietnam context, particularly in the primary school sector. This study aims to examine the impact of Michigan leadership behaviors on organizational citizenship behaviors (OCBs)…
Descriptors: Foreign Countries, Behavior Standards, Elementary Schools, Organizational Culture
Combs, Adam – Journal of Educational Measurement, 2023
A common method of checking person-fit in Bayesian item response theory (IRT) is the posterior-predictive (PP) method. In recent years, more powerful approaches have been proposed that are based on resampling methods using the popular L*[subscript z] statistic. There has also been proposed a new Bayesian model checking method based on pivotal…
Descriptors: Bayesian Statistics, Goodness of Fit, Evaluation Methods, Monte Carlo Methods
Molenaar, Dylan; Cúri, Mariana; Bazán, Jorge L. – Journal of Educational and Behavioral Statistics, 2022
Bounded continuous data are encountered in many applications of item response theory, including the measurement of mood, personality, and response times and in the analyses of summed item scores. Although different item response theory models exist to analyze such bounded continuous data, most models assume the data to be in an open interval and…
Descriptors: Item Response Theory, Data, Responses, Intervals
Joseph A. Rios; Jiayi Deng – Educational and Psychological Measurement, 2025
To mitigate the potential damaging consequences of rapid guessing (RG), a form of noneffortful responding, researchers have proposed a number of scoring approaches. The present simulation study examines the robustness of the most popular of these approaches, the unidimensional effort-moderated (EM) scoring procedure, to multidimensional RG (i.e.,…
Descriptors: Scoring, Guessing (Tests), Reaction Time, Item Response Theory
Roya Shoahosseini; Purya Baghaei; Hossein Khodabakhshzadeh; Hamid Ashraf – Language Testing in Asia, 2024
C-Test is a gap-filling test designed to measure first and second language proficiency. Over the past four decades, researchers have shown the fit of C-Test data to parametric item response theory (IRT) models, but no study so far has shown the fit of C-Tests to nonparametric IRT models. The purpose of this study is to contribute to the ongoing…
Descriptors: Item Response Theory, Nonparametric Statistics, Language Proficiency, Second Language Learning
Daniel McNeish; Melissa G. Wolf – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Despite the popularity of traditional fit index cutoffs like RMSEA [less than or equal to] 0.06 and CFI [greater than or equal to] 0.95, several studies have noted issues with overgeneralizing traditional cutoffs. Computational methods have been proposed to avoid overgeneralization by deriving cutoffs specifically tailored to the characteristics…
Descriptors: Structural Equation Models, Cutting Scores, Generalizability Theory, Error of Measurement