using 'lrm' for logistic regression

Hi R,

I am getting this error while trying to use 'lrm' function with nine
independent variables:

res =
lrm(y1994~WC08301+WC08376+WC08316+WC08311+WC01001+WC08221+WC08106+WC0810
1+WC08231,data=y)

singular information matrix in lrm.fit (rank= 8 ).  Offending
variable(s):

WC08101 WC08221 

Error in j:(j + params[i] - 1) : NA/NaN argument

Now, if I take choose only four independent variables then there is no
error.

res = lrm(y1994~ WC08221+WC08106+WC08101+WC08231,data=y)

But strangely, if I use 'glm', with the family as binomial(logit) and
with the same dataset, it is working perfectly fine.

res =
glm(y1994~WC08301+WC08376+WC08316+WC08311+WC01001+WC08221+WC08106+WC0810
1+WC08231,data=y,family=binomial(logit))

Any ideas..?

Regards

Utkarsh
Design's fitting functions are not kind about ignoring parameters 
associated with singular covariance matrices.  In glm you should see a 
zero for such coefficients.  In design you have to delete the singular 
variables manually.  Occasionally you have to tweak the tol argument to lrm.

A new function in Hmisc called redun will run a redundancy analysis to 
help understand the predictor collinearities.

Frank

This e-mail may contain confidential and/or privileged i...{{dropped:13}}

______________________________________________
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.

Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University

using 'lrm' for logistic regression

Thread (2 messages)