[R] Finding out collinearity in regression

From: Young Cho <iidn01_at_yahoo.com>
Date: Thu 30 Jun 2005 - 13:45:48 EST

Hi, I am trying to find out a collinearity in explanatory variables with alias().

I creat a dataframe:

dat <- ds[,sapply(ds,nlevels)>=2]
dat$Y <- Response

Explanatory variables are factor and response is continuous random variable. When I run a regression, I have the following error:

fit <- aov( Y ~ . , data = dat)
Error in "contrasts<-"(`*tmp*`, value =
"contr.treatment") :

        contrasts can be applied only to factors with 2 or more levels

I think there is a dependency in explanatory variables. So, I wanted to use alias to find out a dependency in design matrix but I can't because I cannot create "fit" in the first place.

One of examples I found is:

carprice1.lm <- lm(gpm100 ~
Type+Min.Price+Price+Max.Price+Range.Price,data=carprice) alias(carprice1.lm)

But, what if I can create lm object ? Then is there a way to find out a dependency in design matrix? Thanks a lot for help in advance!


R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Jun 30 13:51:20 2005

This archive was generated by hypermail 2.1.8 : Fri 03 Mar 2006 - 03:33:07 EST