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Peer reviewedRasmussen, Jeffrey Lee – Applied Psychological Measurement, 1988
The performance was studied of five small-sample statistics--by F. M. Lord, W. Kristof, Q. McNemar, R. A. Forsyth and L. S. Feldt, and J. P. Braden--that test whether two variables measure the same trait except for measurement error. Effects of non-normality were investigated. The McNemar statistic was most powerful. (TJH)
Descriptors: Error of Measurement, Monte Carlo Methods, Psychometrics, Sample Size
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
