I'm running brglm with binomial loguistic regression. The perhaps multicollinearity-related feature(s) are:
(1) the k IVs are all binary categorical, coded as 0 or 1; (2) each row of the IVs contains exactly C (< k) 1's; (3) k IVs, there are n * k unique rows; (4) when brglm is run, at least 1 IV is reported as involving a singularity. I've tried recoding the n IV's using (n-1) indicator variables: brglm produces a result without reporting singularities. How should I go about computing estimates for the offending IVs? Is there a better way? I'm interested primarily in the reliability of the parameter estimates. -- View this message in context: http://www.nabble.com/Multicollinearity-with-brglm--tp22814696p22814696.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.
