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Bilge Bal-Sezerel; Deniz Arslan; Ugur Sak – Measurement: Interdisciplinary Research and Perspectives, 2025
In this study, the factorial invariance of the ASIS (Anadolu-Sak Intelligence Scale) was examined across time. Data were obtained from there groups of first-grade students who were administered the ASIS in 2020, 2021, and 2022. The analyses were conducted using multisample confirmatory factor analyses. Factorial invariance was tested with six…
Descriptors: Intelligence Tests, Grade 1, Factor Structure, Scores
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
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
Edwards, Michael C. – Measurement: Interdisciplinary Research and Perspectives, 2013
This author has had the privilege of knowing Professor Maydeu-Olivares for almost a decade and although their paths cross only occasionally, such instances were always enjoyable and enlightening. Edwards states that Maydeu-Olivares' target article for this issue, ("Goodness-of-Fit Assessment of Item Response Theory Models") provides…
Descriptors: Goodness of Fit, Item Response Theory, Models, Factor Analysis
Maydeu-Olivares, Alberto – Measurement: Interdisciplinary Research and Perspectives, 2013
The article provides an overview of goodness-of-fit assessment methods for item response theory (IRT) models. It is now possible to obtain accurate "p"-values of the overall fit of the model if bivariate information statistics are used. Several alternative approaches are described. As the validity of inferences drawn on the fitted model…
Descriptors: Goodness of Fit, Item Response Theory, Models, Maximum Likelihood Statistics
Raykov, Tenko – Measurement: Interdisciplinary Research and Perspectives, 2010
Mroch, Suh, Kane, & Ripkey (2009); Suh, Mroch, Kane, & Ripkey (2009); and Kane, Mroch, Suh, & Ripkey (2009) provided elucidating discussions on critical properties of linear equating methods under the nonequivalent groups with anchor test (NEAT) design. In this popular equating design, two test forms are administered to different…
Descriptors: Equated Scores, Test Items, Factor Analysis, Models
Henson, Robert A. – Measurement: Interdisciplinary Research and Perspectives, 2009
The paper by Drs. Rupp and Templin provides a much needed step toward the general application of diagnostic classification modeling (DCMs). The authors have provided a summary of many of the concepts that one must consider to properly apply a DCM (which ranges from model selection and estimation, to assessing the appropriateness of the model using…
Descriptors: Classification, Psychometrics, Evaluation, Models
Widaman, Keith F.; Grimm, Kevin J. – Measurement: Interdisciplinary Research and Perspectives, 2009
Nesselroade, Gerstorf, Hardy, and Ram developed a new and interesting way to enforce invariance at the second-order level in P-technique models, while allowing first-order structure to stray from invariance. We discuss our concerns with this approach under the headings of falsifiability, the nature of manifest variables included in models, and…
Descriptors: Factor Structure, Models, Factor Analysis, Comparative Analysis
Borsboom, Denny; Dolan, Conor V. – Measurement: Interdisciplinary Research and Perspectives, 2007
Nesselroade, Gerstorf, Hardy, and Ram (this issue) propose to "filter out" idiosyncrasies of dynamic processes at the level of the individual through the application of dynamic factor analysis. The problem that they deal with is that individuals may differ in the items that are "salient" for a given construct, so that the same measurement model…
Descriptors: Factor Structure, Factor Analysis, Individual Differences, Models
West, Stephen G.; Ryu, Ehri – Measurement: Interdisciplinary Research and Perspectives, 2007
Nomothetic and idiographic approaches to research have long been in tension. John Nesselroade et al. have been at the forefront of a constructive rapprochement between these traditions. Heretofore their efforts have assumed a common measurement structure across persons. They have primarily focused on modeling relationships within persons, which…
Descriptors: Measurement Techniques, Factor Analysis, Models, Patients
Rupp, Andre A.; Templin, Jonathan L. – Measurement: Interdisciplinary Research and Perspectives, 2008
"Diagnostic classification models" (DCM) are frequently promoted by psychometricians as important modelling alternatives for analyzing response data in situations where multivariate classifications of respondents are made on the basis of multiple postulated latent skills. In this review paper, a definitional boundary of the space of DCM…
Descriptors: Factor Analysis, Classification, Item Response Theory, Psychometrics
Maris, Gunter; Bechger, Timo – Measurement: Interdisciplinary Research and Perspectives, 2009
Rupp and Templin (2008) do a good job at describing the ever expanding landscape of Diagnostic Classification Models (DCM). In many ways, their review article clearly points to some of the questions that need to be answered before DCMs can become part of the psychometric practitioners toolkit. Apart from the issues mentioned in this article that…
Descriptors: Factor Analysis, Classification, Psychometrics, Item Response Theory