Do you have a reason to treat all 3 levels together and not have a separate regression for each level?
--- On Tue, 1/7/08, rlearner309 <[EMAIL PROTECTED]> wrote: > From: rlearner309 <[EMAIL PROTECTED]> > Subject: [R] A regression problem using dummy variables > To: r-help@r-project.org > Received: Tuesday, 1 July, 2008, 11:38 PM > This is actually more like a Statistics problem: > I have a dataset with two dummy variables controlling three > levels. The > problem is, one level does not have many observations > compared with other > two levels (a couple of data points compared with 1000+ > points on other > levels). When I run the regression, the result is bad. I > have unbalanced > SE and VIF. Does this kind of problem also belong to > "near sigularity" > problem? Does it make any difference if I code the level > that lacks data > (0,0) in stead of (0,1)? > > thanks a lot! > -- > View this message in context: > http://www.nabble.com/A-regression-problem-using-dummy-variables-tp18214377p18214377.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. ______________________________________________ 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.
