Statistical Power Analysis, 5th Edition

5 Correlation and Regression

DOI: 10.4324/9781003296225-5

There is a clear link between correlation and regression analysis and the broader topic of power analysis because both are concerned fundamentally with effect sizes. Throughout this book, we have used the percentage of variance in the dependent variable that is explained by treatments, interventions, or other variables (i.e., PV) as our main effect size measure. If you square the correlation between two variables, X and Y, what you get is PV – i.e., the proportion of variance in Y that is explained by X. Similarly, in multiple regression, where several X variables are used to predict scores on Y, the squared multiple correlation coefficient (i.e., R²) is a measure of the proportion of ...