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Kelvin T. Afolabi; Timothy R. Konold – Practical Assessment, Research & Evaluation, 2024
Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given…
Descriptors: Measurement Techniques, Factor Analysis, Structural Equation Models, Comparative Analysis
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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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Tenko Raykov; Christine DiStefano; Lisa Calvocoressi – Educational and Psychological Measurement, 2024
This note demonstrates that the widely used Bayesian Information Criterion (BIC) need not be generally viewed as a routinely dependable index for model selection when the bifactor and second-order factor models are examined as rival means for data description and explanation. To this end, we use an empirically relevant setting with…
Descriptors: Bayesian Statistics, Models, Decision Making, Comparative 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
Christopher E. Shank – ProQuest LLC, 2024
This dissertation compares the performance of equivalence test (EQT) and null hypothesis test (NHT) procedures for identifying invariant and noninvariant factor loadings under a range of experimental manipulations. EQT is the statistically appropriate approach when the research goal is to find evidence of group similarity rather than group…
Descriptors: Factor Analysis, Goodness of Fit, Intervals, Comparative Analysis
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Markus T. Jansen; Ralf Schulze – Educational and Psychological Measurement, 2024
Thurstonian forced-choice modeling is considered to be a powerful new tool to estimate item and person parameters while simultaneously testing the model fit. This assessment approach is associated with the aim of reducing faking and other response tendencies that plague traditional self-report trait assessments. As a result of major recent…
Descriptors: Factor Analysis, Models, Item Analysis, Evaluation Methods
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Lopez, J.; Johnson, C.; Dai, L.; Jones, M. H.; Nodine, M.; Cooper, D.; Eckel, S. – Journal of Psychoeducational Assessment, 2023
The present study examined the convergent validity between two frequently used achievement goal instruments: Patterns of Adaptive Learning Scales (PALS) and the Achievement Goal Questionnaire 3 x 2 (AGQ 3 x 2). Confirmatory factor analysis and structural equation models tested for relationships both within and across the scales in a sample of…
Descriptors: Surveys, Academic Achievement, Goal Orientation, Test Validity
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Aidoo, Eric Nimako; Appiah, Simon K.; Boateng, Alexander – Journal of Experimental Education, 2021
This study investigated the small sample biasness of the ordered logit model parameters under multicollinearity using Monte Carlo simulation. The results showed that the level of biasness associated with the ordered logit model parameters consistently decreases for an increasing sample size while the distribution of the parameters becomes less…
Descriptors: Statistical Bias, Monte Carlo Methods, Simulation, Sample Size
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Antonio Fabio Bella – Journal of Moral Education, 2024
I present a new model of the self-regulation of virtue that integrates perspectives on emotion, cognition, and motivation. Across three vignette-based studies in US/UK (N = 1,540), I developed through exploratory and confirmatory factor analysis a multi-item measure of broadening and defensive responses, the Self-Regulation of Virtue Inventory…
Descriptors: Moral Values, Moral Development, Metacognition, Network Analysis
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Fu, Yuanshu; Wen, Zhonglin; Wang, Yang – Educational and Psychological Measurement, 2022
Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is…
Descriptors: Comparative Analysis, Structural Equation Models, Factor Analysis, Reliability
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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
Merkle, Edgar C.; Fitzsimmons, Ellen; Uanhoro, James; Goodrich, Ben – Grantee Submission, 2021
Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…
Descriptors: Bayesian Statistics, Structural Equation Models, Psychometrics, Factor Analysis
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Mao, Jih-Yu; Xiao, Jincen; Liu, Xin; Qing, Tao; Xu, Hongling – Creativity Research Journal, 2023
In this research, we explore how coworker ideation levels or, more specifically, the average ideation levels of coworkers within a workgroup affect a focal employee's ideation. We examine an underlying mechanism and a boundary condition of this influence process. Drawing on social cognitive theory, we argue that high coworker ideation levels are…
Descriptors: Work Environment, Employee Attitudes, Creativity, Self Efficacy
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Wang, Ze – Large-scale Assessments in Education, 2022
In educational and psychological research, it is common to use latent factors to represent constructs and then to examine covariate effects on these latent factors. Using empirical data, this study applied three approaches to covariate effects on latent factors: the multiple-indicator multiple-cause (MIMIC) approach, multiple group confirmatory…
Descriptors: Comparative Analysis, Evaluation Methods, Grade 8, Mathematics Achievement
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Xu, Tianxi; Qian, Xueqin; Rifenbark, Graham G.; Shogren, Karrie A.; Hagiwara, Mayumi – Intellectual and Developmental Disabilities, 2022
This study explores the psychometric properties of "Self-Determination Inventory: Student Report" (SDI:SR) in students with intellectual and developmental disabilities (IDD) and without disabilities in China. The paper-and-pencil version of SDI:SR Chinese Translation (SDI:SR Chinese) was used to explore self-determination across students…
Descriptors: Foreign Countries, Psychometrics, Self Determination, Intellectual Disability
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