Hi Michael, You can just fit your model, and then use anova() to get the Sum of Squares.
## fit and store model m <- lm(mpg ~ hp * wt * vs, data = mtcars) ## store ANOVA from model msum <- anova(m) ## divide all Sums of Squares by the sum() of the Sums of Squares msum[["Sum Sq"]]/sum(msum[["Sum Sq"]]) do note that this will be order dependent. HTH, Josh On Sat, Mar 26, 2011 at 4:03 AM, Michael Haenlein <[email protected]> wrote: > Dear all, > > is there a convenient way to determine the effect size for a regression > coefficient in a multiple regression model? > I have a model of the form lm(y ~ A*B*C*D) and would like to determine > Cohen's f2 (http://en.wikipedia.org/wiki/Effect_size) for each predictor > without having to do it manually. > > Thanks, > > Michael > > > > Michael Haenlein > Associate Professor of Marketing > ESCP Europe > Paris, France > > [[alternative HTML version deleted]] > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Joshua Wiley Ph.D. Student, Health Psychology University of California, Los Angeles http://www.joshuawiley.com/ ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
