1. This is a statistics, not an R, question. Post on a statistics list, like stats.stackexchange.com
Also... On Wed, Nov 21, 2012 at 12:39 PM, Torvon <tor...@gmail.com> wrote: > I run 9 WLS regressions in R, with 7 predictors each. > > What I want to do now is compare: > (1) The strength of predictors within each model (assuming all predictors > are significant). That is, I want to say whether x1 is stronger than x2, > and also say whether it is **significantly stronger.** -- I have no idea what this means, though perhaps it is defined somewhere and in some way that I am not familiar with. When you post to a stats list, I suggest you provide a reference so the folks there know what you mean by this. -- Bert I compare strength by > simply comparing standardized beta weights, correct? How do I compare if > one predictor is significantly stronger than the others? I thought about > comparing confidence intervals, but if I understand correctly the > confidence intervals are calculated from the unstandardized beta weights, > which in this case would not help me, correct? > (2) The strength of the same predictor over different models. I want to say > whether x1 affects y1 - y9 equally strong or not. How would I do this? > > I hope that I provided all information that is needed. > Thank you > T > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ 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.
