The Experts below are selected from a list of 2067 Experts worldwide ranked by ideXlab platform
Penfield, Randall D. - One of the best experts on this subject based on the ideXlab platform.
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Confidence Intervals For An Effect Size When Variances Are Not Equal
DigitalCommons@WayneState, 2006Co-Authors: Algina James, Keselman H. J., Penfield, Randall D.Abstract:Confidence intervals must be robust in having nominal and actual Probability Coverage in close agreement. This article examined two ways of computing an effect size in a two-group problem: (a) the classic approach which divides the mean difference by a single standard deviation and (b) a variant of a method which replaces least squares values with robust trimmed means and a Winsorized variance. Confidence intervals were determined with theoretical and bootstrap critical values. Only the method that used robust estimators and a bootstrap critical value provided generally Accurate Probability Coverage under conditions of nonnormality and variance heterogeneity in balanced as well as unbalanced designs
Algina James - One of the best experts on this subject based on the ideXlab platform.
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Confidence Intervals For An Effect Size When Variances Are Not Equal
DigitalCommons@WayneState, 2006Co-Authors: Algina James, Keselman H. J., Penfield, Randall D.Abstract:Confidence intervals must be robust in having nominal and actual Probability Coverage in close agreement. This article examined two ways of computing an effect size in a two-group problem: (a) the classic approach which divides the mean difference by a single standard deviation and (b) a variant of a method which replaces least squares values with robust trimmed means and a Winsorized variance. Confidence intervals were determined with theoretical and bootstrap critical values. Only the method that used robust estimators and a bootstrap critical value provided generally Accurate Probability Coverage under conditions of nonnormality and variance heterogeneity in balanced as well as unbalanced designs
Keselman H. J. - One of the best experts on this subject based on the ideXlab platform.
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Confidence Intervals For An Effect Size When Variances Are Not Equal
DigitalCommons@WayneState, 2006Co-Authors: Algina James, Keselman H. J., Penfield, Randall D.Abstract:Confidence intervals must be robust in having nominal and actual Probability Coverage in close agreement. This article examined two ways of computing an effect size in a two-group problem: (a) the classic approach which divides the mean difference by a single standard deviation and (b) a variant of a method which replaces least squares values with robust trimmed means and a Winsorized variance. Confidence intervals were determined with theoretical and bootstrap critical values. Only the method that used robust estimators and a bootstrap critical value provided generally Accurate Probability Coverage under conditions of nonnormality and variance heterogeneity in balanced as well as unbalanced designs
