When obtaining ANOVA results with SPSS we also get a R-squared and an adjusted R-squared. For a multi-way ANOVA the eta-squared is given per factor or interaction.

The measures are criticized by - among others - Andy Field:

"However, this measure of effect size is slightly biased because it is based purely on sums of squares from the sample and no adjustment is made for the fact that we're trying to estimate the effect size in the population."

He proposes to use the omega-squared. Especially when running Multi-way ANOVA's it causes a lot of extra work to calculate the omega-squares for all factors and interactions. Because ... SPSS does not give you omega-squares, so you have to calculate them by hand. As far as I know, omega-squared is also not in R.

My question: how wrong is it to simply use the measures given by SPSS?

Other question: what's the difference between R-squared and the adjusted R-squared?

Best regards,

Wilbert