Thanks, I'll try to put my hands on the reference By the way, would it be easier if I just checked out the code by which the glm function computes the residuals? Or maybe this is not a very good idea. And if it is, how can I check out the source, I never really found out!
jason Dr. Iasonas Lamprianou Assistant Professor (Educational Research and Evaluation) Department of Education Sciences European University-Cyprus P.O. Box 22006 1516 Nicosia Cyprus Tel.: +357-22-713178 Fax: +357-22-590539 Honorary Research Fellow Department of Education The University of Manchester Oxford Road, Manchester M13 9PL, UK Tel. 0044 161 275 3485 iasonas.lampria...@manchester.ac.uk --- On Fri, 20/8/10, David Winsemius <dwinsem...@comcast.net> wrote: > From: David Winsemius <dwinsem...@comcast.net> > Subject: Re: [R] Deviance Residuals > To: "Iasonas Lamprianou" <lampria...@yahoo.com> > Cc: r-help@r-project.org > Date: Friday, 20 August, 2010, 13:20 > > On Aug 20, 2010, at 5:54 AM, Iasonas Lamprianou wrote: > > > Dear all, > > > > I am running a logistic regression and this is the > output: > > > > glm(formula = educationUniv ~ brncntr, family = > binomial) > > > > Deviance Residuals: > > Min > 1Q Median > 3Q Max # > αυτά είναι τα υπόλοιπα > > -0.8825 -0.7684 > -0.7684 1.5044 1.6516 > > > > Coefficients: > > Estimate Std. > Error z value Pr(>|z|) > > (Intercept) -1.06869 0.01155 > -92.487 <2e-16 *** > > brncntrNo 0.32654 > 0.03742 8.726 <2e-16 > *** > > --- > > Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 > '.' 0.1 ' ' 1 > > > > (Dispersion parameter for binomial family taken to be > 1) > > > > Null deviance: 49363 on 42969 degrees of > freedom > > Residual deviance: 49289 on 42968 degrees > of freedom > > AIC: 49293 > > > > > > I thought that the residuals should all be restricted > in the range 0 to 1 (since I am predicting a binary > outcome). > > The internal regression calculations are done on the > log-odds scale so the working residuals are on that scale. > Those are stored in the glm.obj as the "residuals" item. I > believe that if you tried mean(glm.obj$residuals) you should > get 0. Presumably the deviance residuals are offered > in preference to the working residuals because the deviance > residual's use as an influence measure is made readily > interpretable by reference to chi-square statistics. Page > 205 of the Hastie and Pregibon citation has all the > definitions. > > --David. > > > > > I read many posts on this list and I realized that > there are four(!?) different types of residuals. I need a > simple account of these four types of residuals, if anyone > can help it will be great. > > > > residuals(glm1, "response") > > residuals(glm1, "pearson") > > residuals(glm1, "deviance") > > residuals(glm1, "working") - especially this one > confuses me a lot! > > > > What is the "working" option and how is this > different? > > > > Thank you > > Jason > > > > Dr. Iasonas Lamprianou > > > -- > David Winsemius, MD > West Hartford, CT > > ______________________________________________ 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.