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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
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Willse, John T. – Measurement and Evaluation in Counseling and Development, 2017
This article provides a brief introduction to the Rasch model. Motivation for using Rasch analyses is provided. Important Rasch model concepts and key aspects of result interpretation are introduced, with major points reinforced using a simulation demonstration. Concrete guidelines are provided regarding sample size and the evaluation of items.
Descriptors: Item Response Theory, Test Results, Test Interpretation, Simulation
Powers, Sonya; Li, Dongmei; Suh, Hongwook; Harris, Deborah J. – ACT, Inc., 2016
ACT reporting categories and ACT Readiness Ranges are new features added to the ACT score reports starting in fall 2016. For each reporting category, the number correct score, the maximum points possible, the percent correct, and the ACT Readiness Range, along with an indicator of whether the reporting category score falls within the Readiness…
Descriptors: Scores, Classification, College Entrance Examinations, Error of Measurement
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Fan, Xitao; Sun, Shaojing – Journal of Early Adolescence, 2014
In adolescence research, the treatment of measurement reliability is often fragmented, and it is not always clear how different reliability coefficients are related. We show that generalizability theory (G-theory) is a comprehensive framework of measurement reliability, encompassing all other reliability methods (e.g., Pearson "r,"…
Descriptors: Generalizability Theory, Measurement, Reliability, Correlation
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Kane, Michael – Journal of Educational Measurement, 2011
Errors don't exist in our data, but they serve a vital function. Reality is complicated, but our models need to be simple in order to be manageable. We assume that attributes are invariant over some conditions of observation, and once we do that we need some way of accounting for the variability in observed scores over these conditions of…
Descriptors: Error of Measurement, Scores, Test Interpretation, Testing
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Kolen, Michael J.; Lee, Won-Chan – Educational Measurement: Issues and Practice, 2011
This paper illustrates that the psychometric properties of scores and scales that are used with mixed-format educational tests can impact the use and interpretation of the scores that are reported to examinees. Psychometric properties that include reliability and conditional standard errors of measurement are considered in this paper. The focus is…
Descriptors: Test Use, Test Format, Error of Measurement, Raw Scores
Kane, Michael – 1999
The relationship between generalizability and validity is explained, making four important points. The first is that generalizability coefficients provide upper bounds on validity. The second point is that generalization is one step in most interpretive arguments, and therefore, generalizability is a necessary condition for the validity of these…
Descriptors: Error of Measurement, Generalizability Theory, Test Interpretation, Validity
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Brown, Jonathan R. – Language, Speech, and Hearing Services in Schools, 1989
The importance of using the standard error of measurement (SEm) in determining reliability in test scores is emphasized. The SEm is compared to the hypothetical true score for standardized tests, and procedures for calculation of the SEm are explained. (JDD)
Descriptors: Elementary Secondary Education, Error of Measurement, Scores, Standardized Tests
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Meyer, Kevin D.; Foster, Jeff L. – International Journal of Testing, 2008
With the increasing globalization of human resources practices, a commensurate increase in demand has occurred for multi-language ("global") personality norms for use in selection and development efforts. The combination of data from multiple translations of a personality assessment into a single norm engenders error from multiple sources. This…
Descriptors: Global Approach, Cultural Differences, Norms, Human Resources