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Schweizer, Karl; Gold, Andreas; Krampen, Dorothea – Educational and Psychological Measurement, 2023
In modeling missing data, the missing data latent variable of the confirmatory factor model accounts for systematic variation associated with missing data so that replacement of what is missing is not required. This study aimed at extending the modeling missing data approach to tetrachoric correlations as input and at exploring the consequences of…
Descriptors: Data, Models, Factor Analysis, Correlation
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
Pere J. Ferrando; Ana Hernández-Dorado; Urbano Lorenzo-Seva – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…
Descriptors: Correlation, Factor Analysis, Models, Goodness of Fit
Dobbins, Ian G. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
The recognition memory receiver operating characteristic (ROC) is typically asymmetric with a characteristic elevation of the left-hand portion. Whereas the unequal variance signal detection model (uvsd) assumes the asymmetry results because old item evidence is noisier than new item evidence, the dual process signal detection model (dpsd) assumes…
Descriptors: Acoustics, Recognition (Psychology), Memory, Task Analysis
Qinxin Shi; Jonathan E. Butner; Robyn Kilshaw; Ascher Munion; Pascal Deboeck; Yoonkyung Oh; Cynthia A. Berg – Grantee Submission, 2023
Developmental researchers commonly utilize longitudinal data to decompose reciprocal and dynamic associations between repeatedly measured constructs to better understand the temporal precedence between constructs. Although the cross-lagged panel model (CLPM) is commonly used in developmental research, it has been criticized for its potential to…
Descriptors: Models, Longitudinal Studies, Developmental Psychology, Behavior Problems
Kefayat Delf Loveymi; Rezvan Homaei – Emotional & Behavioural Difficulties, 2024
Today, school bullying is considered an important social problem that causes developmental injuries and health issues in bullies and victims. The present study investigated the mediating role of brain-behavioural systems in relationships between school climate and emotional self-regulation with school bullying in high school students. This study…
Descriptors: Bullying, Educational Environment, Correlation, Victims
Cao, Chunhua; Kim, Eun Sook; Chen, Yi-Hsin; Ferron, John – Educational and Psychological Measurement, 2021
This study examined the impact of omitting covariates interaction effect on parameter estimates in multilevel multiple-indicator multiple-cause models as well as the sensitivity of fit indices to model misspecification when the between-level, within-level, or cross-level interaction effect was left out in the models. The parameter estimates…
Descriptors: Goodness of Fit, Hierarchical Linear Modeling, Computation, Models
Lee, Bitna; Sohn, Wonsook – Educational and Psychological Measurement, 2022
A Monte Carlo study was conducted to compare the performance of a level-specific (LS) fit evaluation with that of a simultaneous (SI) fit evaluation in multilevel confirmatory factor analysis (MCFA) models. We extended previous studies by examining their performance under MCFA models with different factor structures across levels. In addition,…
Descriptors: Goodness of Fit, Factor Structure, Monte Carlo Methods, Factor Analysis
Ben Stenhaug; Ben Domingue – Grantee Submission, 2022
The fit of an item response model is typically conceptualized as whether a given model could have generated the data. We advocate for an alternative view of fit, "predictive fit", based on the model's ability to predict new data. We derive two predictive fit metrics for item response models that assess how well an estimated item response…
Descriptors: Goodness of Fit, Item Response Theory, Prediction, Models
Rebecca M. Stone – ProQuest LLC, 2021
Much research exists pertaining to psychological help-seeking behaviors and intentions in the United States (U.S.; Levinson & Ifrah, 2010; Vogel & Wester, 2003; Wendt & Shafer, 2015; AEgisdottir & Gerstein, 2009), yet little research considers comprehensive models of psychological help-seeking behaviors and intentions in the United…
Descriptors: Mental Health, Help Seeking, Correlation, Intention
Juan, Liu Xin; Tao, Wu Yun; Veloo, Palanisamy K.; Supramaniam, Mahadevan – SAGE Open, 2022
Dishonest academic behavior (DAB) by students in Chinese higher education institutions has become a significant concern. However, the related study of academic dishonesty in mainland China is very limited. This study fills this gap by examining the theory of planned behavior and its three extended versions, validating the effectiveness of…
Descriptors: Prediction, Models, Cheating, Behavior Theories
Tipsrirach, Phalad; Thacha, Witoon; Chusorn, Prayuth – Education Quarterly Reviews, 2021
This research aimed at creating a structural model of the indicators of Educational Leadership for Primary School Principals in Thailand, which is considered to be a theoretical model that has been used to test for coherence with the empirical data collected from a sample group of 580 participants, who were selected from 30,719 Primary School…
Descriptors: Instructional Leadership, Elementary Schools, Principals, Models
Arens, A. Katrin; Jansen, Malte; Preckel, Franzis; Schmidt, Isabelle; Brunner, Martin – Review of Educational Research, 2021
The structure of academic self-concept (ASC) is assumed to be multidimensional and hierarchical. This methodological review considers the most central models depicting the structure of ASC: a higher-order factor model, the Marsh/Shavelson model, the nested Marsh/Shavelson model, a bifactor representation based on exploratory structural equation…
Descriptors: Foreign Countries, High School Students, Self Concept, Models
Chung, Seungwon; Houts, Carrie – Measurement: Interdisciplinary Research and Perspectives, 2020
Advanced modeling of item response data through the item response theory (IRT) or item factor analysis frameworks is becoming increasingly popular. In the social and behavioral sciences, the underlying structure of tests/assessments is often multidimensional (i.e., more than 1 latent variable/construct is represented in the items). This review…
Descriptors: Item Response Theory, Evaluation Methods, Models, Factor Analysis
Lúcio, Patrícia Silva; Vandekerckhove, Joachim; Polanczyk, Guilherme V.; Cogo-Moreira, Hugo – Journal of Psychoeducational Assessment, 2021
The present study compares the fit of two- and three-parameter logistic (2PL and 3PL) models of item response theory in the performance of preschool children on the Raven's Colored Progressive Matrices. The test of Raven is widely used for evaluating nonverbal intelligence of factor g. Studies comparing models with real data are scarce on the…
Descriptors: Guessing (Tests), Item Response Theory, Test Validity, Preschool Children