[R] More Logistic Regression Tools?

[Ramón Casero Cañas]

Frank E Harrell Jr wrote:
> Eric Rescorla <ekr at rtfm.com> wrote:
> 
>> (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 


The documentation of the Design package, section residuals.lrm, says

<CITE>
Details
    For the goodness-of-fit test, the le Cessie-van Houwelingen normal
test statistic for the unweighted
    sum of squared errors (Brier score times n) is used.
</CITE>

It is not clear to me whether the test implemented is for the statistic
with a constant kernel described in

S. le Cessie and J.C. van Houwelingen. A goodness-of-fit test for binary
regression models, based on smoothing methods. Biometrics, 47:1267­1282,
Dec 1991.

or the variation in

D.W. Hosmer, T. Hosmer, S. Le Cessie, and S. Lemeshow. A comparison of
goodness-of-fit tests for the logistic regression model. Statistics in
Medicine, 16:965­980, 1997.

Sorry, I couldn't get this from looking at the code either (I'm quite
new to R). Is the statistic tested the T defined by le Cessie and van
Houwelingen?

Regards,

-- 
Ramón Casero Cañas

http://www.robots.ox.ac.uk/~rcasero/wiki
http://www.robots.ox.ac.uk/~rcasero/blog