[R] [Q] Goodness-of-fit test of a logistic regression model using rms package

[Frank Harrell]

On Wed, 1 Sep 2010, GMail (KU) wrote:

> Hello,
>
> I was looking for a way to evaluate the goodness-of-fit of a logistic regression model. After googling, I found that I could use "resid(fit, 'gof')" method implemented in the rms package. However, since I am not used to the "le Cessie-van Houwelingen normal test statistic," I do not know which statistic from the returned from the "resid(fit, 'gof')" call that I could use to evaluate the goodness of fit.
>
> When I ran the "resid(fit, 'gof')", I got the following results:
> ##############################################
> Sum of squared errors     Expected value|H0                    SD
>          6844.684594           6805.672315              2.790969
>                    Z                     P
>            13.978043              0.000000
> ##############################################
>
> I tried to read the le Cessie and van Houwelingen's original paper, but I found that it required prerequisite knowledge I don't current have.
> Could someone explain how to interpret the results from "resid(fit, 'gof') call?
>
> Any help would be much appreciated.
>
> Young-Jin Lee

Young-Jin,

I think everyone has trouble interpreting omnibus tests of lack of 
fit, so don't feel bad.  You just know that something somewhere is 
probably wrong with the model.  I focus on directed tests such as 
allowing all continuous variables to have nonlinear effects or 
allowing selected interactions, and finding out how important the 
complex model terms are.

Frank Harrell