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Peer reviewedBowers, John – Educational and Psychological Measurement, 1971
Descriptors: Error of Measurement, Mathematical Models, Test Reliability, True Scores
Peer reviewedGardner, P. L. – Journal of Educational Measurement, 1970
Descriptors: Error of Measurement, Mathematical Models, Statistical Analysis, Test Reliability
Peer reviewedHuynh, Huynh – Journal of Educational Statistics, 1981
Simulated data based on five test score distributions indicate that a slight modification of the asymptotic normal theory for the estimation of the p and kappa indices in mastery testing will provide results which are in close agreement with those based on small samples from the beta-binomial distribution. (Author/BW)
Descriptors: Error of Measurement, Mastery Tests, Mathematical Models, Test Reliability
Peer reviewedBrennan, Robert L.; Prediger, Dale J. – Educational and Psychological Measurement, 1981
This paper considers some appropriate and inappropriate uses of coefficient kappa and alternative kappa-like statistics. Discussion is restricted to the descriptive characteristics of these statistics for measuring agreement with categorical data in studies of reliability and validity. (Author)
Descriptors: Classification, Error of Measurement, Mathematical Models, Test Reliability
Peer reviewedWilcox, Rand R. – Journal of Educational Statistics, 1981
Both the binomial and beta-binomial models are applied to various problems occurring in mental test theory. The paper reviews and critiques these models. The emphasis is on the extensions of the models that have been proposed in recent years, and that might not be familiar to many educators. (Author)
Descriptors: Error of Measurement, Item Analysis, Mathematical Models, Test Reliability
Peer reviewedPeng, Chao-Ying, J.; Subkoviak, Michael J. – Journal of Educational Measurement, 1980
Huynh (1976) suggested a method of approximating the reliability coefficient of a mastery test. The present study examines the accuracy of Huynh's approximation and also describes a computationally simpler approximation which appears to be generally more accurate than the former. (Author/RL)
Descriptors: Error of Measurement, Mastery Tests, Mathematical Models, Statistical Analysis
Peer reviewedYarnold, Paul R. – Educational and Psychological Measurement, 1984
Unreliable profiles impose the difficulty that ordinal and interval relations among the individual's scores become uncertain or unstable. A profile reliability coefficient is derived to estimate the relative expected extent of this ordinal and interval "inversion" for any profile of K measures. (Author/DWH)
Descriptors: Error of Measurement, Mathematical Models, Profiles, Test Reliability
Peer reviewedWilliams, Richard H.; Zimmerman, Donald W. – Journal of Experimental Education, 1982
A mathematical link between test reliability and test validity is derived, taking into account the correlation between error scores on a test and error scores on a criterion measure. When this correlation is positive, the "paradoxical" nonmonotonic relation between test reliability and test validity occurs universally. (Author/BW)
Descriptors: Correlation, Error of Measurement, Mathematical Models, Test Reliability
Peer reviewedStrauss, David – Educational and Psychological Measurement, 1981
To determine if the observed correlation between two variables can be "explained" by a third variable, a significance test on the partial correlation coefficient is often used. This can be misleading when the third variable is measured with error. This article shows how the problem can be partially overcome. (Author/BW)
Descriptors: Correlation, Error of Measurement, Mathematical Models, Predictive Validity
Peer reviewedZimmerman, Donald W.; And Others – Journal of Experimental Education, 1981
Reliability coefficients of linear combinations of observed scores have anomalous properties which have led to difficulties in the investigation of difference scores and gain scores in test theory. Discrepancies between classical results and correct results obtained from more general formulas, which allow for correlated errors, are examined…
Descriptors: Error of Measurement, Mathematical Formulas, Mathematical Models, Scores
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 reviewedZimmerman, Donald W.; And Others – Journal of Experimental Education, 1984
Three types of test were compared: a completion test, a matching test, and a multiple-choice test. The completion test was more reliable than the matching test, and the matching test was more reliable than the multiple-choice test. (Author/BW)
Descriptors: Comparative Analysis, Error of Measurement, Higher Education, Mathematical Models
PDF pending restorationLam, Tony C. M. – 1981
The objective of this paper is to examine the relationship between the unreliability of difference scores and the power of tests of significance in an attempt to determine the validity of the paradox for the measurement of change presented by Overall and Woodward: that the power of tests of significance is maximum when the reliability of the…
Descriptors: Achievement Gains, Correlation, Error of Measurement, Hypothesis Testing
Peer reviewedWhitely, Susan E. – Journal of Educational Measurement, 1977
A debate concerning specific issues and the general usefulness of the Rasch latent trait test model is continued. Methods of estimation, necessary sample size, and the applicability of the model are discussed. (JKS)
Descriptors: Error of Measurement, Item Analysis, Mathematical Models, Measurement
Peer reviewedFeldt, Leonard S. – Educational and Psychological Measurement, 1984
The binomial error model includes form-to-form difficulty differences as error variance and leads to Ruder-Richardson formula 21 as an estimate of reliability. If the form-to-form component is removed from the estimate of error variance, the binomial model leads to KR 20 as the reliability estimate. (Author/BW)
Descriptors: Achievement Tests, Difficulty Level, Error of Measurement, Mathematical Formulas


