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.lampria...@manchester.ac.uk
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