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Yao, Lihua – Applied Psychological Measurement, 2013
Through simulated data, five multidimensional computerized adaptive testing (MCAT) selection procedures with varying test lengths are examined and compared using different stopping rules. Fixed item exposure rates are used for all the items, and the Priority Index (PI) method is used for the content constraints. Two stopping rules, standard error…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
Lee, Won-Chan – Applied Psychological Measurement, 2007
This article introduces a multinomial error model, which models an examinee's test scores obtained over repeated measurements of an assessment that consists of polytomously scored items. A compound multinomial error model is also introduced for situations in which items are stratified according to content categories and/or prespecified numbers of…
Descriptors: Simulation, Error of Measurement, Scoring, Test Items
Peer reviewedWhitely, Susan E. – Applied Psychological Measurement, 1979
A model which gives maximum likelihood estimates of measurement error within the context of a simplex model for practice effects is presented. The appropriateness of the model is tested for five traits, and error estimates are compared to the classical formula estimates. (Author/JKS)
Descriptors: Error of Measurement, Error Patterns, Higher Education, Mathematical Models
Peer reviewedSamejima, Fumiko – Applied Psychological Measurement, 1977
Several important implications in latent trait theory, with implications for individualized or tailored testing, are pointed out. A way of using the information function in tailored testing in connection with the standard error estimation of the ability level using maximum likelihood estimation is suggested. (Author/JKS)
Descriptors: Adaptive Testing, Career Development, Error of Measurement, Item Analysis
Peer reviewedZimmerman, Donald W.; And Others – Applied Psychological Measurement, 1993
Some of the methods originally used to find relationships between reliability and power associated with a single measurement are extended to difference scores. Results, based on explicit power calculations, show that augmenting the reliability of measurement by reducing error score variance can make significance tests of difference more powerful.…
Descriptors: Equations (Mathematics), Error of Measurement, Individual Differences, Mathematical Models
Peer reviewedHumphreys, Lloyd G.; And Others – Applied Psychological Measurement, 1993
Two articles discuss the controversy about the relationship between reliability and the power of significance tests in response to the discussion of Donald W. Zimmerman, Richard H. Williams, and Bruno D. Zumbo. Lloyd G. Humphreys emphasizes the differences between what statisticians can do and constraints on researchers. Zimmerman, Williams, and…
Descriptors: Error of Measurement, Individual Differences, Power (Statistics), Research Methodology
Peer reviewedKleinke, David J. – Applied Psychological Measurement, 1979
Lord's, Millman's and Saupe's methods of approximating the standard error of measurement are reviewed. Through an empirical demonstration involving 200 university classroom tests, all three approximations are shown to be biased. (Author/JKS)
Descriptors: Error of Measurement, Error Patterns, Higher Education, Mathematical Formulas
Peer reviewedLevin, Joel R.; Subkoviak, Michael J. – Applied Psychological Measurement, 1977
Textbook calculations of statistical power or sample size follow from formulas that assume that the variables under consideration are measured without error. However, in the real world of behavioral research, errors of measurement cannot be neglected. The determination of sample size is discussed, and an example illustrates blocking strategy.…
Descriptors: Analysis of Covariance, Analysis of Variance, Error of Measurement, Hypothesis Testing
Peer reviewedMellenbergh, Gideon J.; van der Linden, Wim J. – Applied Psychological Measurement, 1979
For six tests, coefficient delta as an index for internal optimality is computed. Internal optimality is defined as the magnitude of risk of the decision procedure with respect to the true score. Results are compared with an alternative index (coefficient kappa) for assessing the consistency of decisions. (Author/JKS)
Descriptors: Classification, Comparative Analysis, Decision Making, Error of Measurement
Peer reviewedWhitely, Susan E. – Applied Psychological Measurement, 1979
Two sources of inconsistency were separated by reanalyzing data from a major study on short-term consistency. Little evidence was found for generalizability or behavioral predictability. Results supported the assumption that measurement error from short-term fluctuations is not due to systematic individual differences in response consistency.…
Descriptors: Behavior Change, Cognitive Processes, College Freshmen, Error of Measurement

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