It is true that our lives are complex but we have to stick to principles. Plus, statisticians have the lowest unemployment rate in all of the sciences (1% according to NSF from a poll taken 2 years ago) so we should be able to capitalize on that by sticking to well-founded beliefs and facts and choosing positions were respect for our expertise is a given.
Standardized coefficients cloud rather than clarify, and they only apply to the trivial case where everything is linear. See http://biostat.mc.vanderbilt.edu/ManuscriptChecklist for more information. Frank Jeroen Ooms wrote: > > Unfortunately I found myself in the same position as outlined above, where > I was requested to reproduce 'standardized regression coefficients' as > reported by SPSS. Below an example that produces something very similar to > the results table from an SPSS "Linear Regression" procedure, including > the standardized regression coefficients: > > mylm <- lm(Sepal.Width ~ ., data=iris, x=TRUE, y=TRUE) > sd.x <- sd(mylm$x); > sd.y <- sd(mylm$y); > std.coef <- coef(mylm) * (sd.x / sd.y); > coef.table <- as.data.frame(summary(mylm)$coefficients); > coef.table <- cbind(coef.table, std.coef); > print(coef.table); > > I do agree with B.R. but unfortunately the life of an applied statistician > is complex sometimes :-) > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Standardized-beta-coefficients-in-regression-tp791616p3843763.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.