Re: [R] More Logistic Regression Tools?

From: Ramón Casero Cañas <8-T_at_gmx.net>
Date: Fri 07 Apr 2006 - 07:26:22 EST


Frank E Harrell Jr wrote:
> Eric Rescorla <ekr@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

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Received on Fri Apr 07 07:54:09 2006

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