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Throughout the Best Evidence Encyclopedia, the term “effect size” (ES) is used. This is the difference between the mean of the experimental group and the mean of the control group (after adjustment for any pretest differences), divided by the standard deviation of the control group. When means or standard deviations are not reported, ES is often estimated from other information that is available.
What is considered a large effect size? There is no universally accepted definition. More is better, but often the quality of the research design is more important than the size of the effect. For example, a large experiment with random assignment to treatments that obtained an effect size of +0.20 is more important than a small, matched experiment with an effect size of +0.90. Small and matched studies are more likely to have unreliable, possibly biased findings, while you can rely on the positive effect size in the large, randomized study.
One way to interpret the size of difference indicated by an effect size is to consider the improvement in percentile scores that would take place if a program with a given effect size is implemented. The table below shows this:
An effect size of… Would increase percentile scores from:
An effect size of… |
Would increase percentile
scores from: |
+0.10 |
50 to 54 |
+0.20 |
50 to 58 |
+0.30 |
50 to 62 |
+0.40
|
50 to 66 |
+0.50
|
50 to 69 |
+0.60
|
50 to 73 |
+0.70
|
50 to 76 |
+0.80
|
50 to 79 |
+0.90
|
50 to 82 |
+1.00 |
50 to 84 |
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