ERIC Number: EJ773675
Record Type: Journal
Publication Date: 2007
Pages: 17
Abstractor: Author
ISBN: N/A
ISSN: ISSN-0022-0973
EISSN: N/A
Is the Pearson r[squared] Biased, and if So, What Is the Best Correction Formula?
Wang, Zhongmiao; Thompson, Bruce
Journal of Experimental Education, v75 n2 p109-125 Win 2007
In this study the authors investigated the use of 5 (i.e., Claudy, Ezekiel, Olkin-Pratt, Pratt, and Smith) R[squared] correction formulas with the Pearson r[squared]. The authors estimated adjustment bias and precision under 6 x 3 x 6 conditions (i.e., population [rho] values of 0.0, 0.1, 0.3, 0.5, 0.7, and 0.9; population shapes normal, skewness = kurtosis = 1, and skewness = -1.5 with kurtosis = 3.5; ns = 10, 20, 40, 60, 100, and 200 respectively). Results indicate that the sample Pearson r[squared] is marginally biased at small sample sizes and small population effect sizes, and that the Ezekiel and the Smith R[squared] corrections work well in controlling this bias. (Contains 5 tables.)
Descriptors: Effect Size, Correlation, Mathematical Formulas, Monte Carlo Methods, Least Squares Statistics, Error Correction, Error of Measurement, Statistical Bias, Simulation, Research Design, Investigations, Structural Equation Models
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: Researchers
Language: English
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