The Journal of Experimental Education · 2007 · 32 citations · 27 references
Public HealthBiostatisticsEducational MeasurementExperimental DesignPsychometricsStatisticsBias ControlBias CorrectionEffect Size EstimationSample SizeStatistical AnalysisTest BiasPearson Correlation CoefficientSampling Bias AdjustmentSelection Bias AssessmentSelection Bias CorrectionSmall Population EffectsSmall Population SizeSmall-sample Bias CorrectionStatistical Bias Correction
In this study the authors investigated the use of 5 (i.e., Claudy, Ezekiel, Olkin-Pratt, Pratt, and Smith) R 2 correction formulas with the Pearson r 2. The authors estimated adjustment bias and precision under 6 X 3 X 6 conditions (i.e., population ρ values of .0, .1, .3, .5, .7, and .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 2 is marginally biased at small sample sizes and small population effect sizes, and that the Ezekiel and the Smith R 2 corrections work well in controlling this bias.
27
Primary, Secondary, and Meta-Analysis of Research
Gene V. Glass · Educational Researcher · 1976 · 4.7K citations
The Handbook of Research Synthesis.
D. Howel, H. Cooper, Larry V. Hedges · Biometrics · 1995 · 3.7K citations
Parametric measures of effect size.
Robert Rosenthal · 1994 · 1.6K citations