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Hsin-Yun Lee; You-Lin Chen; Li-Jen Weng – Journal of Experimental Education, 2024
The second version of Kaiser's Measure of Sampling Adequacy (MSA[subscript 2]) has been widely applied to assess the factorability of data in psychological research. The MSA[subscript 2] is developed in the population and little is known about its behavior in finite samples. If estimated MSA[subscript 2]s are biased due to sampling errors,…
Descriptors: Error of Measurement, Reliability, Sampling, Statistical Bias
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Williams, 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
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Williams, Richard H.; Zimmerman, Donald W. – Journal of Experimental Education, 1984
This paper provides a list of 10 salient features of the standard error of measurement, contrasting it to the reliability coefficient. It is concluded that the standard error of measurement should be regarded as a primary characteristic of a mental test. (Author/DWH)
Descriptors: Educational Testing, Error of Measurement, Evaluation Methods, Psychological Testing
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Williams, Richard H.; Zimmerman, Donald W. – Journal of Experimental Education, 1980
It is suggested that error of measurement cannot be routinely incorporated into the "error term" in statistical tests, and that the reliability of test scores does not have the simple relationship to statistical inference that one might expect. (Author/GK)
Descriptors: Error of Measurement, Hypothesis Testing, Mathematical Formulas, Test Reliability
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Zimmerman, 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
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Williams, Richard H.; And Others – Journal of Experimental Education, 1987
Because of limitations in simple gain scores, pychometrists have proposed alternate methods for measuring change, two of which are residualized difference and base-free change. This paper provides large sample empirical estimates of the reliability these change measures. It checks theoretical predictions derived from inequalities involving all…
Descriptors: Error of Measurement, Estimation (Mathematics), Measurement Techniques, Pretests Posttests
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Zimmerman, 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
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Helvey, T. Charles – Journal of Experimental Education, 1975
This article describes a new testing method which can be used to screen learning-deficient children fast, reliably, and inexpensively out of any population of public school systems. (Editor)
Descriptors: Bayesian Statistics, Electroencephalography, Error of Measurement, Intelligence Tests
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Lei, Pui-Wa; Koehly, Laura M. – Journal of Experimental Education, 2003
Classification studies are important for practitioners who need to identify individuals for specialized treatment or intervention. When interventions are irreversible or misclassifications are costly, information about the proficiency of different classification procedures becomes invaluable. This study furnishes information about the relative…
Descriptors: Monte Carlo Methods, Classification, Discriminant Analysis, Regression (Statistics)