It will change the coefficients from lm and therefore their t-values but it will not change the residuals, fitted values, R-squared, F statistic, etc. For example, try this:
set.seed(1) x <- 1:10 y <- x + rnorm(10) lm0 <- lm(y ~ x) # without scale lms <- lm(y ~ scale(x)) # with scale all.equal(fitted(lm0), fitted(lms)) # TRUE # note what the is the same and what is different summary(lm0) summary(lms) Another use of scale is comparing graphs. library(tseries) data(USeconomic) ts.plot(scale(USeconomic), col = 1:4) # compare with ts.plot(USeconomic, col = 1:4) On 3/5/06, Kum-Hoe Hwang <[EMAIL PROTECTED]> wrote: > HOwdy > > I read R books about scale function for variable transformation. > Acoording to this book > scale function leads me to better regression results. Or am I worng? > > I hope somebody tell me about a scale function? > Is it for variable transformation? > > > > > -- > Kum-Hoe Hwang, Phone : 82-31-250-3516Email : [EMAIL PROTECTED] > > [[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 > ______________________________________________ [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
