[R] Deviance Residuals

[Iasonas Lamprianou]

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(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


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.lamprianou at manchester.ac.uk