Unstandardized Effect Sizes

  • Gideon J. MellenberghEmail author


Standardized effect sizes are frequently used, for example, in sample size planning and meta-analysis. However, they are often hard to interpret, and can be estimated in different ways. A measure that is better to interpret than the standardized difference of two means is the probability of superiority. The probability of superiority of paired (e.g., pretest and posttest) scores is the probability that of a randomly selected pair of scores the second (e.g., posttest) score is larger than the first (e.g., pretest) score. The probability of superiority of independent (e.g., E- and C-group) scores is the probability that a randomly selected participant from one (e.g., The E-) group has a larger score than a randomly selected participant from the other (e.g., C-) group. The interpretability of observed test scores is facilitated by applying linear transformations to the scores. Two transformations are described. The Average Item Score (AIS) is the mean of the item scores of the test. The Proportion of Maximum Possible (POMP) score is the proportion that the observed test score takes of the distance between the minimum and maximum possible scores of the test.


Average item score (AIS) transformation Probability of superiority Proportion of maximum possible (POMP) score transformation Unstandardized difference of means 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Emeritus Professor Psychological Methods, Department of PsychologyUniversity of AmsterdamAmsterdamThe Netherlands

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