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Sohee Kim; Ki Lynn Cole – International Journal of Testing, 2025
This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…
Descriptors: Item Response Theory, Comparative Analysis, Models, Item Analysis
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Yasuhiro Yamamoto; Yasuo Miyazaki – Journal of Experimental Education, 2025
Bayesian methods have been said to solve small sample problems in frequentist methods by reflecting prior knowledge in the prior distribution. However, there are dangers in strongly reflecting prior knowledge or situations where much prior knowledge cannot be used. In order to address the issue, in this article, we considered to apply two Bayesian…
Descriptors: Sample Size, Hierarchical Linear Modeling, Bayesian Statistics, Prior Learning
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Nathan A. Call; Alec M. Bernstein; Matthew J. O'Brien; Kelly M. Schieltz; Loukia Tsami; Dorothea C. Lerman; Wendy K. Berg; Scott D. Lindgren; Mark A. Connelly; David P. Wacker – Journal of Applied Behavior Analysis, 2024
Clinicians report primarily using functional behavioral assessment (FBA) methods that do not include functional analyses. However, studies examining the correspondence between functional analyses and other types of FBAs have produced inconsistent results. In addition, although functional analyses are considered the gold standard, their…
Descriptors: Functional Behavioral Assessment, Evaluation Methods, Young Children, Autism Spectrum Disorders
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Kazuhiro Yamaguchi – Journal of Educational and Behavioral Statistics, 2025
This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…
Descriptors: Models, Classification, Bayesian Statistics, Evaluation Methods
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Lingbo Tong; Wen Qu; Zhiyong Zhang – Grantee Submission, 2025
Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…
Descriptors: Factor Analysis, Monte Carlo Methods, Statistical Analysis, Sample Size
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Jiaying Xiao; Chun Wang; Gongjun Xu – Grantee Submission, 2024
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…
Descriptors: Error of Measurement, Models, Evaluation Methods, Item Analysis
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Tenko Raykov – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This note demonstrates that measurement invariance does not guarantee meaningful and valid group comparisons in multiple-population settings. The article follows on a recent critical discussion by Robitzsch and Lüdtke, who argued that measurement invariance was not a pre-requisite for such comparisons. Within the framework of common factor…
Descriptors: Error of Measurement, Prerequisites, Factor Analysis, Evaluation Methods
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Leal, Sharon; Vrij, Aldert; Deeb, Haneen; Fisher, Ronald P. – Applied Cognitive Psychology, 2023
Interviewees sometimes deliberately omit reporting some information. Such omission lies differ from other lies because all the information interviewees present may be entirely truthful. Truth tellers and lie tellers carried out a mission. Truth tellers reported the entire mission truthfully. Lie tellers were also entirely truthful but left out one…
Descriptors: Interviews, Deception, Ethics, Disclosure
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Hussain, Zawar; Cheema, Salman Arif; Hussain, Ishtiaq – Sociological Methods & Research, 2022
This article is about making correction in Tarray, Singh, and Zaizai model and further improving it when stratified random sampling is necessary. This is done by using optional randomized response technique in stratified sampling using a combination of Mangat and Singh, Mangat, and Greenberg et al. models. The suggested model has been studied…
Descriptors: Comparative Analysis, Models, Surveys, Questionnaires
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Baumgartner, Michael; Ambühl, Mathias – Sociological Methods & Research, 2023
Consistency and coverage are two core parameters of model fit used by configurational comparative methods (CCMs) of causal inference. Among causal models that perform equally well in other respects (e.g., robustness or compliance with background theories), those with higher consistency and coverage are typically considered preferable. Finding the…
Descriptors: Causal Models, Evaluation Methods, Goodness of Fit, Scores
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Bartholomew, Scott R.; Mentzer, Nathan; Jones, Matthew; Sherman, Derek; Baniya, Sweta – International Journal of Technology and Design Education, 2022
Traditional efforts around improving assessment often center on the teacher as the evaluator of work rather than the students. These assessment efforts typically focus on measuring learning rather than stimulating, promoting, or producing learning in students. This paper summarizes a study of a large sample of undergraduate students (n = 550) in…
Descriptors: Undergraduate Students, Evaluation Methods, Learning, Comparative Analysis
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James Ohisei Uanhoro – Educational and Psychological Measurement, 2024
Accounting for model misspecification in Bayesian structural equation models is an active area of research. We present a uniquely Bayesian approach to misspecification that models the degree of misspecification as a parameter--a parameter akin to the correlation root mean squared residual. The misspecification parameter can be interpreted on its…
Descriptors: Bayesian Statistics, Structural Equation Models, Simulation, Statistical Inference
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Shunji Wang; Katerina M. Marcoulides; Jiashan Tang; Ke-Hai Yuan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A necessary step in applying bi-factor models is to evaluate the need for domain factors with a general factor in place. The conventional null hypothesis testing (NHT) was commonly used for such a purpose. However, the conventional NHT meets challenges when the domain loadings are weak or the sample size is insufficient. This article proposes…
Descriptors: Hypothesis Testing, Error of Measurement, Comparative Analysis, Monte Carlo Methods
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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
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Lucy Chambers; Sylvia Vitello; Carmen Vidal Rodeiro – Assessment in Education: Principles, Policy & Practice, 2024
In England, some secondary-level qualifications comprise non-exam assessments which need to undergo moderation before grading. Currently, moderation is conducted at centre (school) level. This raises challenges for maintaining the standard across centres. Recent technological advances enable novel moderation methods that are no longer bound by…
Descriptors: Foreign Countries, Evaluation Methods, Comparative Analysis, Grading
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