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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
Hoang V. Nguyen; Niels G. Waller – Educational and Psychological Measurement, 2024
We conducted an extensive Monte Carlo study of factor-rotation local solutions (LS) in multidimensional, two-parameter logistic (M2PL) item response models. In this study, we simulated more than 19,200 data sets that were drawn from 96 model conditions and performed more than 7.6 million rotations to examine the influence of (a) slope parameter…
Descriptors: Monte Carlo Methods, Item Response Theory, Correlation, Error of Measurement
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
Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
Pere J. Ferrando; David Navarro-González; Fabia Morales-Vives – Educational and Psychological Measurement, 2025
The problem of local item dependencies (LIDs) is very common in personality and attitude measures, particularly in those that measure narrow-bandwidth dimensions. At the structural level, these dependencies can be modeled by using extended factor analytic (FA) solutions that include correlated residuals. However, the effects that LIDs have on the…
Descriptors: Scores, Accuracy, Evaluation Methods, Factor Analysis
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
Yeon Ha Kim – Journal of Early Adolescence, 2025
This study aimed to introduce an ego-resiliency questionnaire for preadolescents (the ER-P) by restructuring the ER89 using the data of 1398 preadolescents from the Panel Study on Korean Children. The ER-P was proposed as a 10-item second-order instrument with two factors (Optimal Regulation and Openness to Life Experiences). The ER-P achieved…
Descriptors: Self Concept, Resilience (Psychology), Preadolescents, Asians
Kane, Michael T. – ETS Research Report Series, 2021
Ordinary least squares (OLS) regression provides optimal linear predictions of a dependent variable, y, given an independent variable, x, but OLS regressions are not symmetric or reversible. In order to get optimal linear predictions of x given y, a separate OLS regression in that direction would be needed. This report provides a least squares…
Descriptors: Least Squares Statistics, Regression (Statistics), Prediction, Geometric Concepts
Raykov, Tenko; Marcoulides, George A.; Li, Tenglong – Educational and Psychological Measurement, 2018
This note extends the results in the 2016 article by Raykov, Marcoulides, and Li to the case of correlated errors in a set of observed measures subjected to principal component analysis. It is shown that when at least two measures are fallible, the probability is zero for any principal component--and in particular for the first principal…
Descriptors: Factor Analysis, Error of Measurement, Correlation, Reliability
Affum-Osei, Emmanuel; Mensah, Henry Kofi; Forkuoh, Solomon Kwarteng; Asante, Eric Adom – International Journal of Testing, 2021
The purpose of this study was to examine the psychometric properties of the goal orientation (GO) scale across job search contexts to facilitate its use in large and varied search settings. A sample of 720 job losers and new entrants' job seekers in Ghana completed the survey. Confirmatory factor analysis supported the three-factor theoretical…
Descriptors: Goal Orientation, Job Search Methods, Psychometrics, Factor Analysis
Montoya, Amanda K.; Edwards, Michael C. – Educational and Psychological Measurement, 2021
Model fit indices are being increasingly recommended and used to select the number of factors in an exploratory factor analysis. Growing evidence suggests that the recommended cutoff values for common model fit indices are not appropriate for use in an exploratory factor analysis context. A particularly prominent problem in scale evaluation is the…
Descriptors: Goodness of Fit, Factor Analysis, Cutting Scores, Correlation
Finch, W. Holmes – Educational and Psychological Measurement, 2020
Exploratory factor analysis (EFA) is widely used by researchers in the social sciences to characterize the latent structure underlying a set of observed indicator variables. One of the primary issues that must be resolved when conducting an EFA is determination of the number of factors to retain. There exist a large number of statistical tools…
Descriptors: Factor Analysis, Goodness of Fit, Social Sciences, Comparative Analysis
Ali Derakhshan; Jalil Fathi – Iranian Journal of Language Teaching Research, 2024
This study examined the interconnections between perceived teacher support, student selfregulation, and psychological well-being among undergraduate English majors in Iran (n = 347). Confirmatory factor analysis (CFA) validated the measurement model, demonstrating sound internal consistency as well as convergent and discriminant validity. Harman's…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Well Being
von Oertzen, Timo; Schmiedek, Florian; Voelkle, Manuel C. – Journal of Intelligence, 2020
Properties of psychological variables at the mean or variance level can differ between persons and within persons across multiple time points. For example, cross-sectional findings between persons of different ages do not necessarily reflect the development of a single person over time. Recently, there has been an increased interest in the…
Descriptors: Cognitive Ability, Individual Differences, Statistical Analysis, Factor Analysis
Factor Structure and Psychometric Properties of the Digital Stress Scale in a Chinese College Sample
Chunlei Gao; Mingqing Jian; Ailin Yuan – SAGE Open, 2024
The Digital Stress Scale (DSS) is used to measure digital stress, which is the perceived stress and anxiety associated with social media use. In this study, the Chinese version of the DSS was validated using a sample of 721 Chinese college students, 321 males and 400 females (KMO = 0.923; Bartlett = 5,058.492, p < 0.001). Confirmatory factor…
Descriptors: Factor Structure, Factor Analysis, Psychometrics, Anxiety