Hi David This should do the trick:
data <- cbind(height, sex, age) data.scaled <- data.frame(apply(data, 2, scale)) fit.scaled <- lm(height ~ age + sex - 1, data = data.scaled) summary(fit.scaled) HTH Jo ====================================================================== Hello everybody, Can anyone tell me, how to obtain standardized regression coefficients (betas) for my independent variables when doing a multiple linear regression? height<-c(180,160,150,170,190,172) sex<-c(1,2,2,1,1,2) age<-c(40,20,30,40,20,25) fit<-lm(height~age+sex) summary(fit) I already heard about the "QuantPsyc"-Package, which, unfortunately, produces an error (it says "sd(<data.frame> is deprecated"). Thank you very much! David ______________________________________________ R-help@r-project.org 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.
