(Partial) Eta Squared
When comparing more than two groups of people, we commonly use eta squared or partial eta squared. In a One-Way ANOVA either value can be reported since they will be the same. With other ANOVA analyses, partial eta squared is more appropriate to report. Partial eta squared is telling us how large of an effect the independent variable(s) had on the dependent variable.
Computing Partial Eta Squared
Starting with computing this value by hand, we can again use a formula. As before, there are several different formulas that can be used. Here is just one example:
where:
In order to complete this computation, you must also know how to compute each sum of squares (deviations from the mean), which can be a time-consuming process, especially with larger data sets. As with the other types of effect size, technology can come to the rescue here.
Partial Eta Squared using SPSS
If you're using SPSS 27 or higher, you can opt to include effect size estimates with your ANOVA analysis. Below are a series of images that show you how to include the effect size estimate with the different types of analyses and where to look in the output to locate the value of the effect size:
1) One-Way ANOVA
Here is what you will see in the output:
2) Univariate (located under the "Options" menu)
Here is what's included in the output:
3) Multivariate (located under the "Options" menu)
Here's how it will appear in the output:
4) Repeated Measures (located under the "Options" menu)
Here is how it will appear in the output:
Interpreting the Partial Eta Squared
If no guidelines are provided, you can follow this:
You'll want to review the guidelines provided in your course materials to confirm as there are differing opinions on the thresholds for each effect level.
**For additional assistance with computing and interpreting the effect size for your analysis, attend the SPSS: ANOVA/MANOVA group session**
