Thanks, Professor.

But is it ok to write residuals in the right hand side of the logistic
regression formula? Some people said I cannot since the generalized linear
model is to use a function to link the expectation to a linear model. So
there should not be residuals in the right hand side.

My question is that If residuals do exist (as in the glm model output), why
not put them in the formula (for example, if I write the left-hand side as
the estimated odds-ratio)?

Many thanks!

Happy Thanksgiving!

On 11/24/05, John Fox <jfox@mcmaster.ca> wrote:
>
> Dear Urania,
>
> The residuals method for glm objects can compute several kinds of
> residuals;
> the default is deviance residuals. See ?residuals.glm for details and
> references.
>
> I hope this helps.
> John
>
> --------------------------------
> John Fox
> Department of Sociology
> McMaster University
> Hamilton, Ontario
> Canada L8S 4M4
> 905-525-9140x23604
> http://socserv.mcmaster.ca/jfox
> --------------------------------
>
> > -----Original Message-----
> > From: r-help-bounces@stat.math.ethz.ch
> > [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Urania Sun
> > Sent: Thursday, November 24, 2005 1:36 PM
> > To: r-help@stat.math.ethz.ch
> > Subject: [R] residuals in logistic regression model
> >
> > In the logistic regression model, there is no residual
> >
> > log (pi/(1-pi)) = beta_0 + beta_1*X_1 + .....
> >
> > But glm model will return
> >
> > residuals
> >
> > What is that?
> >
> > How to understand this? Can we put some residual in the
> > logistic regression model by replacing pi with pi' (the estimated pi)?
> >
> >  log (pi'/(1-pi')) = beta_0 + beta_1*X_1 + .....+ ei
> >
> > Thanks!
> >
> >       [[alternative HTML version deleted]]
> >
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>
>

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