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| In 2025 | 1 |
| Since 2024 | 2 |
| Since 2021 (last 5 years) | 3 |
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| Daniel McNeish | 3 |
| Melissa G. Wolf | 1 |
| Roy Levy | 1 |
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| Reports - Research | 3 |
| Journal Articles | 2 |
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Direct linkRoy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
Daniel McNeish; Melissa G. Wolf – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Despite the popularity of traditional fit index cutoffs like RMSEA [less than or equal to] 0.06 and CFI [greater than or equal to] 0.95, several studies have noted issues with overgeneralizing traditional cutoffs. Computational methods have been proposed to avoid overgeneralization by deriving cutoffs specifically tailored to the characteristics…
Descriptors: Structural Equation Models, Cutting Scores, Generalizability Theory, Error of Measurement
Daniel McNeish – Grantee Submission, 2023
Scale validation is vital to psychological research because it ensures that scores from measurement scales represent the intended construct. Factor analysis fit indices are commonly used to provide quantitative evidence that a proposed factor structure is plausible. However, there is mismatch between guidelines for evaluating fit of factor models…
Descriptors: Factor Analysis, Goodness of Fit, Validity, Likert Scales
