... and, furthermore, in most real world situations there are several -- or even "lots" -- of quite different, incomparable models that give essentially equivalent fits. Distinguishing among the alternatives typically requires focused studies designed for the task.
Indeed, as Brian Joiner remarked a long time ago (in a galaxy far away), "Often, even the data aren't sufficient." (This a cryptic statistical "in" joke; example for the in-crowd: is it an outlier or an indication of curvature?). Cheers, Bert Bert Gunter Genentech Nonclinical Statistics On Wed, Sep 1, 2010 at 12:22 PM, Frank Harrell <f.harr...@vanderbilt.edu> wrote: > > > > 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 > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.