Frank E Harrell Jr wrote: > Eric Rescorla <[EMAIL PROTECTED]> 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 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html