that's enough, thank you now I need to do some more background reading... cheers
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, John Fox <j...@mcmaster.ca> wrote: > From: John Fox <j...@mcmaster.ca> > Subject: RE: [R] Deviance Residuals > To: "'Iasonas Lamprianou'" <lampria...@yahoo.com> > Cc: r-help@r-project.org > Date: Friday, 20 August, 2010, 13:14 > Dear Iasonas, > > > > -----Original Message----- > > From: r-help-boun...@r-project.org > [mailto:r-help-boun...@r-project.org] > On > > Behalf Of Iasonas Lamprianou > > Sent: August-20-10 5:55 AM > > To: r-help@r-project.org > > Subject: [R] Deviance Residuals > > > > 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). 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 on the scale of the response, y - E(y); in a > binary logistic regression, y is 0 or 1 and E(y) is the > fitted probability of a 1. As it turns out, response > residuals aren't terribly useful for a logit model. > > > residuals(glm1, "pearson") > > Components of the Pearson goodness-of-fit statistic. > > > residuals(glm1, "deviance") > > Components of the residual deviance for the model. > > > residuals(glm1, "working") - especially this one > confuses me a lot! > > Residuals from the final weighted-least-squares regression > of the IWLS procedure used to fit the model; useful, for > example, for detecting nonlinearity. > > > > > What is the "working" option and how is this > different? > > See above. > > I hope this helps, > John > > -------------------------------- > John Fox > Senator William McMaster > Professor of Social Statistics > Department of Sociology > McMaster University > Hamilton, Ontario, Canada > web: socserv.mcmaster.ca/jfox > > > > > Thank you > > 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 > > > > > > > > > > ______________________________________________ > > 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.