[R] AUC for logistic regression [was: (no subject)]

[Berton Gunter]

AUC means "Area Under the Curve" and is a common summary statistic for
repeated measures experiments (e.g. repeated measurements of serum
concentration of a drug in an individual)in PK/PD studies
(pharmacokinetic/pharmacodynamic).

I think the poster may actually mean "nonlinear regression for logistic
models" rather than "logistic regression," which, of course, has a different
statistical meaning. Hence nonlinear regression modeling for repeated
measures is probably the issue here, for which nlme() is appropriate, I
think. Alternatively, and perhaps somewhat less statistically desirable
(though perhaps fairly standard in PK/PD modeling), one can use nls() or
perhaps nlsList() to fit each individual's curve and compute the AUC's. So
in any case, the answer appears to be "yes, you can use R" perhaps with
add-ons to do what you want.


-- Bert Gunter
Genentech Non-Clinical Statistics
South San Francisco, CA
 
"The business of the statistician is to catalyze the scientific learning
process."  - George E. P. Box
 
 

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Spencer Graves
> Sent: Wednesday, December 15, 2004 11:07 AM
> To: rrouzier at mdanderson.org
> Cc: R-help at lists.R-project.org
> Subject: Re: [R] AUC for logistic regression [was: (no subject)]
> 
>       What's AUC?  If you mean AIC (Akaike Information 
> Criterion), and 
> if you fit logistic regression using "glm", the help file 
> says that glm 
> returns an object of class "glm", which is a list containing 
> among other 
> things an attribute aic.  For example, suppose you fit a 
> model as follows: 
> 
>       fit <- glm(y~x, famil=binomial()...)
> 
>       Then fit$aic returns the AIC. 
> 
>       You may also wish to consider anova and anova.glm. 
> 
>       hope this helps.  spencer graves
> 
> rrouzier at mdanderson.org wrote:
> 
> >Dear R-helper,
> >
> >I would like to compare the AUC of two logistic regression 
> models (same 
> >population). Is it possible with R ?
> >
> >Thank you
> >
> >Roman Rouzier
> >	[[alternative HTML version deleted]]
> >
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> 
> -- 
> Spencer Graves, PhD, Senior Development Engineer
> O:  (408)938-4420;  mobile:  (408)655-4567
> 
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