For ANOVA one option is the partial eta squared \eta^2_p: \eta^2_p=SSeffect/(SSeffect+SSerror)
For multiple regression (continuous predictors) you might use the standardized parameter estimate, the regression coefficient you obtain standardizing the predictor: the larger the absolute value, the larger the size of the effect. You might take a look at: S. Olejnik and J. Algina, (2003), Generalized eta and omega squared statistics: measures of effect size for some common research designs, Psychol Methods. 8(4):434-47. and, if you have repeated measures: R. Bakeman (2005), Recommended effect size statistics for repeated measures designs, Behavior Research Methods, 37 (3), 379-384. Bruno ----- Original Message ----- From: "Matthew Bridgman" <[EMAIL PROTECTED]> To: <r-help@stat.math.ethz.ch> Sent: Wednesday, June 21, 2006 5:01 PM Subject: [R] effect size > Does anyone know a simple way of calculating effect sizes? > > Thanks > MB > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html