On Wed, 2 Jul 2008, rlearner309 wrote:
I think the covariance between dummy variables or between dummy variables and
intercept should always be zero. meaning: no sigularity problem??
No. You can easily check that this is not true using the cov() function.
Indicator variables for mutually exclusive groups are negatively correlated.
-thomas
rlearner309 wrote:
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-tp18214377p18237666.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.
Thomas Lumley Assoc. Professor, Biostatistics
[EMAIL PROTECTED] University of Washington, Seattle
______________________________________________
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.
