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_at_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.Received on Tue 01 Jul 2008 - 16:29:36 GMT
Archive maintained by Robert King, hosted by
the discipline of
statistics at the
University of Newcastle,
Archive generated by hypermail 2.2.0, at Wed 02 Jul 2008 - 14:31:04 GMT.
Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help. Please read the posting guide before posting to the list.
list of date sections of archive