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Timothy R. Konold; Elizabeth A. Sanders; Kelvin Afolabi – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Measurement invariance (MI) is an essential part of validity evidence concerned with ensuring that tests function similarly across groups, contexts, and time. Most evaluations of MI involve multigroup confirmatory factor analyses (MGCFA) that assume simple structure. However, recent research has shown that constraining non-target indicators to…
Descriptors: Evaluation Methods, Error of Measurement, Validity, Monte Carlo Methods
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Tenko Raykov; Lisa Calvocoressi; Randall E. Schumacker – Measurement: Interdisciplinary Research and Perspectives, 2024
This paper is concerned with the process of selecting between the increasingly popular bi-factor model and the second-order factor model in measurement research. It is indicated that in certain settings widely used in empirical studies, the second-order model is nested in the bi-factor model and obtained from the latter after imposing appropriate…
Descriptors: Factor Analysis, Decision Making, Computer Software, Measurement Techniques
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Karl Schweizer; Andreas Gold; Dorothea Krampen; Stefan Troche – Educational and Psychological Measurement, 2024
Conceptualizing two-variable disturbances preventing good model fit in confirmatory factor analysis as item-level method effects instead of correlated residuals avoids violating the principle that residual variation is unique for each item. The possibility of representing such a disturbance by a method factor of a bifactor measurement model was…
Descriptors: Correlation, Factor Analysis, Measurement Techniques, Item Analysis
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Liu, Xiaoling; Cao, Pei; Lai, Xinzhen; Wen, Jianbing; Yang, Yanyun – Educational and Psychological Measurement, 2023
Percentage of uncontaminated correlations (PUC), explained common variance (ECV), and omega hierarchical ([omega]H) have been used to assess the degree to which a scale is essentially unidimensional and to predict structural coefficient bias when a unidimensional measurement model is fit to multidimensional data. The usefulness of these indices…
Descriptors: Correlation, Measurement Techniques, Prediction, Regression (Statistics)
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Raykov, Tenko; Anthony, James C.; Menold, Natalja – Educational and Psychological Measurement, 2023
The population relationship between coefficient alpha and scale reliability is studied in the widely used setting of unidimensional multicomponent measuring instruments. It is demonstrated that for any set of component loadings on the common factor, regardless of the extent of their inequality, the discrepancy between alpha and reliability can be…
Descriptors: Correlation, Evaluation Research, Reliability, Measurement Techniques
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Branscum, Ann M.; Park, Anna E.; Bihm, Elson M.; Murphy, John J.; Furlong, Michael J. – Psychology in the Schools, 2023
The Social and Emotional Health Survey-Secondary (SEHS-S) is a widely used self-report measure of adolescents' strengths and positive mental health. However, the SEHS-S does not have a proxy (i.e., parent) informant version. A parent form of the SEHS-S could allow school psychologists to gather additional information about students' strengths for…
Descriptors: Test Construction, Test Validity, Mental Health, Parent Attitudes
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Raykov, Tenko; Doebler, Philipp; Marcoulides, George A. – Measurement: Interdisciplinary Research and Perspectives, 2022
This article is concerned with the large-sample parameter estimator behavior in applications of Bayesian confirmatory factor analysis in behavioral measurement. The property of strong convergence of the popular Bayesian posterior median estimator is discussed, which states numerical convergence with probability 1 of the resulting estimates to the…
Descriptors: Bayesian Statistics, Measurement Techniques, Correlation, Factor Analysis
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Raykov, Tenko; DiStefano, Christine; Calvocoressi, Lisa; Volker, Martin – Educational and Psychological Measurement, 2022
A class of effect size indices are discussed that evaluate the degree to which two nested confirmatory factor analysis models differ from each other in terms of fit to a set of observed variables. These descriptive effect measures can be used to quantify the impact of parameter restrictions imposed in an initially considered model and are free…
Descriptors: Effect Size, Models, Measurement Techniques, Factor Analysis
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Savas Varlik – Journal of Baltic Science Education, 2025
This research is a comprehensive mixed-methods study that aims to examine in depth the correlations between science teachers' research literacy, socio-scientific reasoning, and problem-solving skills. The quantitative phase of the research was conducted using a descriptive survey method, while the qualitative phase employed a case study design.…
Descriptors: Research Skills, Scientific Literacy, School Districts, Science Teachers
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Rasooli, Amirhossein; Zandi, Hamed; DeLuca, Christopher – School Psychology Review, 2023
Empirical research in education has largely adopted quantitative approaches to measure teachers' and students' perceptions of fairness and justice in classroom contexts. The purpose of this study is to understand the validity evidence of fairness and justice instruments including how fairness and justice have been conceptualized in measures.…
Descriptors: Measurement Techniques, Ethics, Justice, Validity
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Yongbi Zhi; Ali Derakhshan – Asia-Pacific Education Researcher, 2025
Considering the key role of organizational commitment in teachers' professional performance, many researchers have studied the predictors of this variable in different educational institutions. However, a short glance at the pertinent literature displays that most of the previous studies on this variable have been conducted in general education…
Descriptors: Language Teachers, Self Control, Factor Analysis, Measurement Techniques
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Mustafa Taktak; Görsev Bafrali – International Journal of Technology in Education, 2025
This study aimed to develop a valid and reliable scale to measure individuals' and organizations' attitudes toward the use of ChatGPT, emphasizing the necessity for organizations to adapt to rapidly evolving information and technology environments. The methodology consisted of three stages. In the first stage, a 13-item draft scale was…
Descriptors: Artificial Intelligence, Technology Uses in Education, Factor Analysis, Validity
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D'Urso, E. Damiano; Tijmstra, Jesper; Vermunt, Jeroen K.; De Roover, Kim – Educational and Psychological Measurement, 2023
Assessing the measurement model (MM) of self-report scales is crucial to obtain valid measurements of individuals' latent psychological constructs. This entails evaluating the number of measured constructs and determining which construct is measured by which item. Exploratory factor analysis (EFA) is the most-used method to evaluate these…
Descriptors: Factor Analysis, Measurement Techniques, Self Evaluation (Individuals), Psychological Patterns
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Klein, Leander Luiz; De Guimarães, Julio Cesar Ferro; Severo, Eliana Andréa; Dorion, Eric Charles Henri; Schirmer Feltrin, Thiago – International Journal of Sustainability in Higher Education, 2023
Purpose: As few studies have explored the causal relationship between both the triple bottom line (TBL) of sustainability and the lean practices in higher education institutions (HEIs), the purpose of this paper is to analyze the relationships between lean practices and sustainable practices in Brazilian HEIs. Design/methodology/approach: A survey…
Descriptors: Sustainability, Factor Analysis, Educational Practices, Correlation
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Pallavi Banerjee; Nurullah Eryilmaz – International Journal of Comparative Education and Development, 2024
Purpose: Given the scientific and practical difficulties inherent in measuring and comparing socioeconomic deprivation (SED), and the further complexity added in cross national measurements, the main aim of this paper was to check the validity of SED measures used in PISA 2018 dataset. The SED measure used in PISA 2018 was the PISA index of…
Descriptors: Socioeconomic Status, Cross Cultural Studies, Foreign Countries, Achievement Tests
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