[R] logistic model diagnostics residuals.lrm {design}, residuals()

Frank E Harrell Jr f.harrell at Vanderbilt.Edu
Thu Mar 11 19:25:19 CET 2010

Chaudhari, Bimal wrote:
> I am interested in a model diagnostic for logistic regression which is normally distributed (much like the residuals in linear regression with are ~ N(0,variance unknown).
> My understanding is that most (all?) of the residuals returned by residuals.lrm {design} either don't have a well defined distribution or are distributed as Chi-Square.
> Have I overlooked a residual measure or would it be possible to transform one of the residual measures into something reasonably 'normal' while retaining information from the residual so I could compare between models (obviously I could blom transform any of the measures, but then I'd always get a standard normal)?
> Cheers,
> bimal

Hi Bimal,

What would make it necessary for the residuals to have a certain 
distribution?  Why would you expect a categorical Y variable to give 
risk to residuals with a nice distributions?

You can do residual diagnostics without worrying about the distribution.


> Bimal P Chaudhari, MPH
> MD Candidate, 2011
> Boston University
> MS Candidate, 2010
> Washington University in St Louis
> 	[[alternative HTML version deleted]]
> ______________________________________________
> 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 Chairman        School of Medicine
                      Department of Biostatistics   Vanderbilt University

More information about the R-help mailing list