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.
Frank
Bimal P Chaudhari, MPH
MD Candidate, 2011
Boston University
MS Candidate, 2010
Washington University in St Louis
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