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Dimitrov, Dimiter M. – Educational and Psychological Measurement, 2020
This study presents new models for item response functions (IRFs) in the framework of the D-scoring method (DSM) that is gaining attention in the field of educational and psychological measurement and largescale assessments. In a previous work on DSM, the IRFs of binary items were estimated using a logistic regression model (LRM). However, the LRM…
Descriptors: Item Response Theory, Scoring, True Scores, Scaling
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Raykov, Tenko; Marcoulides, George A. – Educational and Psychological Measurement, 2016
The frequently neglected and often misunderstood relationship between classical test theory and item response theory is discussed for the unidimensional case with binary measures and no guessing. It is pointed out that popular item response models can be directly obtained from classical test theory-based models by accounting for the discrete…
Descriptors: Test Theory, Item Response Theory, Models, Correlation
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MacCann, Robert G. – Educational and Psychological Measurement, 2008
It is shown that the Angoff and bookmarking cut scores are examples of true score equating that in the real world must be applied to observed scores. In the context of defining minimal competency, the percentage "failed" by such methods is a function of the length of the measuring instrument. It is argued that this length is largely…
Descriptors: True Scores, Cutting Scores, Minimum Competencies, Scores
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Bowers, John – Educational and Psychological Measurement, 1971
Descriptors: Error of Measurement, Mathematical Models, Test Reliability, True Scores
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Williams, Richard H.; Zimmerman, Donald W. – Educational and Psychological Measurement, 1977
The usual formulas for the reliability of differences between two test scores are based on the assumption that the error scores are uncorrelated. Formulas are presented for the general case where this assumption is unnecessary. (Author/JKS)
Descriptors: Correlation, Error of Measurement, Error Patterns, Scores
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Cascio, Wayne F.; Kurtines, William M. – Educational and Psychological Measurement, 1977
A test of significance for identifying individuals who are most influenced by an experimental treatment as measured by pre-post test change score is presented. The technique requires true difference scores, the reliability of obtained differences, and their standard error of measurement. (Author/JKS)
Descriptors: Error of Measurement, Measurement Techniques, Pretesting, Pretests Posttests
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Ebel, Robert L. – Educational and Psychological Measurement, 1972
Author supports the credibility of the propositions that: (1) the true component of a score is proportional to the number of equivalent elements that contribute to it. And, (2) the error component of a score is proportional to the square root of the number of equivalent elements that contribute to it. (Author/MB)
Descriptors: Error of Measurement, Item Analysis, Mathematical Applications, Scores
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Cureton, Edward E. – Educational and Psychological Measurement, 1971
A derivation of a formula for the stability coefficient is presented and discussed in terms of test reliability over time. (PR)
Descriptors: Error of Measurement, Raw Scores, Statistical Analysis, Test Reliability
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Glutting, Joseph J.; And Others – Educational and Psychological Measurement, 1987
This paper discusses the basic theory underlying confidence limits and presents reasons why psychologists should incorporate confidence ranges in their psychodiagnostic reports. Four methods for establishing confidence limits are compared. Three of the methods involve estimated true scores, and the fourth is the standard error of measurement…
Descriptors: Error of Measurement, Mathematical Formulas, Psychological Evaluation, Scores
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Cureton, Edward E. – Educational and Psychological Measurement, 1971
A rebuttal of Frary's 1969 article in Educational and Psychological Measurement. (MS)
Descriptors: Error of Measurement, Guessing (Tests), Multiple Choice Tests, Scoring Formulas
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Werts, Charles E.; Linn, Robert L. – Educational and Psychological Measurement, 1972
The general problem of using group status to estimate true scores given multiple measures is considered in this paper. (Authors)
Descriptors: Error of Measurement, Group Status, Mathematical Applications, Multiple Regression Analysis
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Horn, John L. – Educational and Psychological Measurement, 1971
Descriptors: Analysis of Variance, Error of Measurement, Hypothesis Testing, Mathematical Models
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Werts, C. E.; And Others – Educational and Psychological Measurement, 1980
Test-retest correlations can lead to biased reliability estimates when there is instability of true scores and/or when measurement errors are correlated. Using three administrations of the Test of Standard Written English and essay ratings, an analysis is demonstrated which separates true score instability and correlated errors. (Author/BW)
Descriptors: College Freshmen, Error of Measurement, Essay Tests, Higher Education
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Nugent, William R. – Educational and Psychological Measurement, 2006
One of the most important effect sizes used in meta-analysis is the standardized mean difference (SMD). In this article, the conditions under which SMD effect sizes based on different measures of the same construct are directly comparable are investigated. The results show that SMD effect sizes from different measures of the same construct are…
Descriptors: Effect Size, Meta Analysis, True Scores, Error of Measurement
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Werts, C. E.; And Others – Educational and Psychological Measurement, 1976
A procedure is presented for the analysis of rating data with correlated intrajudge and uncorrelated interjudge measurement errors. Correlations between true scores on different rating dimensions, reliabilities for each judge on each dimension and correlations between intrajudge errors can be estimated given a minimum of three raters and two…
Descriptors: Correlation, Data Analysis, Error of Measurement, Error Patterns
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