[R] More Logistic Regression Tools?
Frank E Harrell Jr
fharrell at virginia.edu
Mon Oct 21 21:11:49 CEST 2002
On Mon, 21 Oct 2002 06:26:46 -0700
Eric Rescorla <ekr at rtfm.com> wrote:
> I've been using R to do logistic regresssion, and that's working
> well, but there are two things I haven't figured out how to do.
>
> (1) Is there some pre-existing function that will let you compute the
> odds ratios and confidence intervals for them for a specific fit. I know
> how to do this manually or even write a function that I can call with
> the coefficients and se, but extending the printing function was a
> little more work than I expected.
>
> I.e. I'm looking for something where you'd type
> odds.ratios(fit)
>
> and get:
>
> Coefficient Odds ratio 95% CI
> XXX 5.2 1.5 7.2
>
> etc.
>
library(Design) # see hesweb1.med.virginia.edu/biostat/rms
d <- datadist(mydataframe); options(datadist='d') # defines data ranges etc.
f <- lrm(y ~ ....)
summary(f, age=c(21,65))
# 65:21 year OR (even if age is nonlinear)
# other continuous variables: use quartiles
See all the contrast function in Design.
> (2) I'd like to compute goodness-of-fit statistics for my fit
> (Hosmer-Lemeshow, Pearson, etc.). I didn't see a package that
> did this. Have I missed one?
Hosmer-Lemeshow has low power and relies on arbitrary binning of predicted probabilities. The Hosmer-Le Cessie omnibus test is unique and has more power usually. To get it:
f <- update(f, x=T, y=T)
resid(f, 'gof') # uses residuals.lrm
Frank Harrell
>
> Thanks,
> -Ekr
>
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--
Frank E Harrell Jr Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
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