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Bo Zhang; Jing Luo; Susu Zhang; Tianjun Sun; Don C. Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Oblique bifactor models, where group factors are allowed to correlate with one another, are commonly used. However, the lack of research on the statistical properties of oblique bifactor models renders the statistical validity of empirical findings questionable. Therefore, the present study took the first step to examine the statistical properties…
Descriptors: Correlation, Predictor Variables, Monte Carlo Methods, Statistical Bias
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
James Ohisei Uanhoro – Structural Equation Modeling: A Multidisciplinary Journal, 2024
We present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector using the matrix logarithm function. Bayesian inference about the unbounded vector is performed assuming a multivariate-normal likelihood, with a mean…
Descriptors: Bayesian Statistics, Structural Equation Models, Correlation, Monte Carlo Methods
Linyuan Wang; Arjen de Vetten; Wilfried Admiraal; Roeland van der Rijst – Education and Information Technologies, 2025
In this study, we investigated the relationship between perceived learner control and student engagement in a blended course. Data were collected from 110 s-year bachelor students through weekly questionnaires to gather information about how they perceived their learner control and engagement in various study activities, including reading…
Descriptors: Undergraduate Students, Blended Learning, Teaching Methods, Student Empowerment
Giesselmann, Marco; Schmidt-Catran, Alexander W. – Sociological Methods & Research, 2022
An interaction in a fixed effects (FE) regression is usually specified by demeaning the product term. However, algebraic transformations reveal that this strategy does not yield a within-unit estimator. Instead, the standard FE interaction estimator reflects unit-level differences of the interacted variables. This property allows interactions of a…
Descriptors: Regression (Statistics), Monte Carlo Methods, Correlation, Evaluation Methods
Tam, Katy Y. Y.; Van Tilburg, Wijnand A. P.; Chan, Christian S. – British Journal of Educational Psychology, 2023
Background: Academic boredom is ubiquitous, and it leads to a range of adverse learning outcomes. Given that students often make estimates of how boring lectures are, does anticipating a lecture to be boring shape their actual experience of boredom? Aims: The current research investigated whether anticipated boredom intensifies subsequent boredom…
Descriptors: Lecture Method, Learner Engagement, Student Attitudes, Undergraduate Students
Novak, Josip; Rebernjak, Blaž – Measurement: Interdisciplinary Research and Perspectives, 2023
A Monte Carlo simulation study was conducted to examine the performance of [alpha], [lambda]2, [lambda][subscript 4], [lambda][subscript 2], [omega][subscript T], GLB[subscript MRFA], and GLB[subscript Algebraic] coefficients. Population reliability, distribution shape, sample size, test length, and number of response categories were varied…
Descriptors: Monte Carlo Methods, Evaluation Methods, Reliability, Simulation
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
Ke-Hai Yuan; Zhiyong Zhang – Grantee Submission, 2025
Most methods for structural equation modeling (SEM) focused on the analysis of covariance matrices. However, "Historically, interesting psychological theories have been phrased in terms of correlation coefficients." This might be because data in social and behavioral sciences typically do not have predefined metrics. While proper methods…
Descriptors: Correlation, Statistical Analysis, Models, Tests
John Hattie; Timothy O'Leary – Educational Psychology Review, 2025
The persistence of learning styles as a concept in educational discourse and research is paradoxical, given the overwhelming evidence discrediting the matching hypothesis, the notion that aligning teaching methods with students' preferred learning styles enhances achievement. This paper examines the resurgence of learning styles across…
Descriptors: Cognitive Style, Meta Analysis, Learning Strategies, Correlation
Michelle Anne Rose – ProQuest LLC, 2024
The purpose of this pilot study was to investigate the relationship between North Carolina pre-service music teachers' perceived preparedness to teach online, Technological, Pedagogical, and Content Knowledge (TPACK) score, and online pedagogy instruction included in methods classes. An online survey was emailed to members of the North Carolina…
Descriptors: Preservice Teachers, Music Teachers, Readiness, Teacher Attitudes
Tong-Rong Yang; Li-Jen Weng – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In Savalei's (2011) simulation that evaluated the performance of polychoric correlation estimates in small samples, two methods for treating zero-frequency cells, adding 0.5 (ADD) and doing nothing (NONE), were compared. Savalei tentatively suggested using ADD for binary data and NONE for data with three or more categories. Yet, Savalei's…
Descriptors: Correlation, Statistical Distributions, Monte Carlo Methods, Sample Size
Yan Xia; Xinchang Zhou – Educational and Psychological Measurement, 2025
Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…
Descriptors: Factor Analysis, Statistical Analysis, Evaluation Methods, Sampling
Chan, Kennedy Kam Ho – International Journal of Science Education, 2022
Pedagogical content knowledge (PCK) refers to the content-specific knowledge that teachers use to promote students' learning of specific subject matter. PCK comprises multiple knowledge components that interact with each other when enacted in teachers' instructional practices. For many years, researchers lacked a robust methodological approach to…
Descriptors: Pedagogical Content Knowledge, Science Teachers, Science Education, Teaching Methods
DeGlopper, Kimberly S.; Schwarz, Cara E.; Ellias, Niall J.; Stowe, Ryan L. – Journal of Chemical Education, 2022
To potentially engage students in "doing organic chemistry", organic chemistry courses should foreground weaving together structure- and energy-related ideas to construct causal accounts for phenomena. Here, we investigate whether enrolling in an organic chemistry course that places substantial emphasis ([approximately]50% of total…
Descriptors: Science Instruction, Organic Chemistry, Scientific Concepts, Concept Formation