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Tenko Raykov; George Marcoulides; Randall Schumacker – Measurement: Interdisciplinary Research and Perspectives, 2024
An application of Bayesian factor analysis for evaluation of scale reliability is discussed, which is developed within the framework of latent variable modeling. The method permits direct point and interval estimation of the reliability coefficient of multiple-component measuring instruments using Bayesian inference. The approach allows also point…
Descriptors: Reliability, Bayesian Statistics, Measurement Techniques, Computer Software
Tenko Raykov; George Marcoulides; James Anthony; Natalja Menold – Measurement: Interdisciplinary Research and Perspectives, 2024
A Bayesian statistics-based approach is discussed that can be used for direct evaluation of the popular Cronbach's coefficient alpha as an internal consistency index for multiple-component measuring instruments, as well as for testing its identity to scale reliability. The method represents an application of confirmatory factor analysis within the…
Descriptors: Reliability, Factor Analysis, Bayesian Statistics, Measurement Techniques
Tihomir Asparouhov; Bengt Muthén – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Penalized structural equation models (PSEM) is a new powerful estimation technique that can be used to tackle a variety of difficult structural estimation problems that can not be handled with previously developed methods. In this paper we describe the PSEM framework and illustrate the quality of the method with simulation studies.…
Descriptors: Structural Equation Models, Computation, Factor Analysis, Measurement Techniques
Chunhua Cao; Yan Wang; Eunsook Kim – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterogeneity at the within level, between level, or both levels. This tutorial focuses on explicating the model specification of multilevel FMM that considers…
Descriptors: Hierarchical Linear Modeling, Factor Analysis, Nonparametric Statistics, Statistical Analysis
Edoardo Saccenti – Teaching Statistics: An International Journal for Teachers, 2024
Principal Component Analysis (PCA) is a powerful statistical technique for reducing the complexity of data and making patterns and relationships within the data more easily understandable. By using PCA, students can learn to identify the most important features of a data set, visualize relationships between variables, and make informed decisions…
Descriptors: Factor Analysis, Data Analysis, Information Literacy, Visualization
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
Alexander von Eye; Wolfgang Wiedermann – Merrill-Palmer Quarterly: A Peer Relations Journal, 2024
In this article, we pursue two points of discussion. First, a new illustration is presented of the person-oriented tenet according to which it can be hazardous to generalize to the individual results that are based on the analysis of aggregated data. Second, it is illustrated that taking into account serial dependence information can result in not…
Descriptors: Research Methodology, Generalizability Theory, Generalization, Multivariate Analysis
Proudfoot, Kevin – Journal of Mixed Methods Research, 2023
Inductive/deductive hybrid thematic analysis offers significant opportunities for researchers, but its application within integrative mixed methods research has yet to be fully explored. Firstly, this article contributes by demonstrating the compatibility of inductive/deductive hybrid thematic analysis with quantitative work in a mixed methods…
Descriptors: Mixed Methods Research, Research Methodology, Logical Thinking, Philosophy
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
Dombrowski, Stefan C.; Casey, Corinne – Journal of Psychoeducational Assessment, 2022
This article reviews the administrative, scoring, and psychometric properties of the Wechsler Individual Achievement Test, Fourth Edition (WIAT-4, NCS Pearson, 2020). The WIAT-4 is one of the more commonly administered broadband measures of academic achievement. The instrument was determined to be well-conceptualized, and generally…
Descriptors: Achievement Tests, Testing, Scoring, Psychometrics
Jon-Paul Paolino – Teaching Statistics: An International Journal for Teachers, 2024
This article presents a novel approach to introducing principal component analysis (PCA), using summary tables and descriptive statistics. Given its applicability across a variety of academic disciplines, this topic offers abundant opportunity for class discussion and activities. However, teaching PCA in an introductory class can be challenging…
Descriptors: Statistics Education, Factor Analysis, Teaching Methods, Introductory Courses
Waller, Niels G. – Journal of Educational and Behavioral Statistics, 2023
Although many textbooks on multivariate statistics discuss the common factor analysis model, few of these books mention the problem of factor score indeterminacy (FSI). Thus, many students and contemporary researchers are unaware of an important fact. Namely, for any common factor model with known (or estimated) model parameters, infinite sets of…
Descriptors: Statistics Education, Multivariate Analysis, Factor Analysis, Factor Structure
Sideridis, Georgios D.; Jaffari, Fathima – Measurement and Evaluation in Counseling and Development, 2022
The utility of the maximum likelihood F-test was demonstrated as an alternative to the omnibus Chi-square test when evaluating model fit in confirmatory factor analysis with small samples, as it has been well documented that the likelihood ratio test (T[subscript ML]) with small samples is not Chi-square distributed.
Descriptors: Maximum Likelihood Statistics, Factor Analysis, Alternative Assessment, Sample Size
Philipp Sterner; Kim De Roover; David Goretzko – Structural Equation Modeling: A Multidisciplinary Journal, 2025
When comparing relations and means of latent variables, it is important to establish measurement invariance (MI). Most methods to assess MI are based on confirmatory factor analysis (CFA). Recently, new methods have been developed based on exploratory factor analysis (EFA); most notably, as extensions of multi-group EFA, researchers introduced…
Descriptors: Error of Measurement, Measurement Techniques, Factor Analysis, Structural Equation Models
Amber M. Hupp – Journal of Chemical Education, 2023
In this paper, a problem set activity focused on understanding and applying unsupervised and supervised chemometric methods for the analysis of biodiesel-diesel blended fuels is described. This problem set was utilized in two upper-level analytical elective courses aimed for junior and senior level students. The data set consists of peak areas…
Descriptors: Chemistry, Science Instruction, Teaching Methods, Fuels