η2 is a commonly used effect size estimate. It describes the proportion of the total variability in a data set that is associated with an effect. Its value is zero when there is no effect and 1.0 when the effect accounts for 100% of the total variability. η2 is most often used in association with analysis of variance and can be calculated from the analysis of variance summary table.
η2 = Sum of squares effect Sum of squares total.
[Page 607]η2 can also be calculated from published F ratios, as long as all F ratios in the design are reported. Jacob Cohen provided general guidelines for what constitutes small (η2 = .01), medium (η2 = .06), and large (η2 = .14) effect sizes in many areas of ...
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