Re: st: Residuals in Logistic Regression

[Richard Williams <Richard.A.Williams.5@nd.edu>]

At 09:26 AM 4/9/2004 -0500, Richard Williams wrote:

> I obviously don't understand how the residual statistics work in logistic 
> regression.  I have run a logistic regression of happymar (coded 0, 1) on 
> church and female (also both 0, 1) and educ (years of education).  I then 
> use predict to get the deviance residuals (I get similar results if I use 
> the rstandard or residuals options on predict).  I get the following:
>
> . extremes  dev p happymar church female educ, nolabel high
>
>   +----------------------------------------------------------------+
>   | obs:        dev          p   happymar   church   female   educ |
>   |----------------------------------------------------------------|
>   |  43.   1.170689   .5039612          1        1        0     10 |
>   |   2.   1.394511   .3782007          1        0        1     10 |
>   |   6.     2.4859   .0858805          0        0        0     11 |
>   |  13.     2.4859   .0858805          1        0        0     11 |
>   |  36.     2.4859   .0858805          1        0        0     11 |
>   +----------------------------------------------------------------+
To follow up on my own message:  I ran the same logistic regression in 
SPSS, and its residuals statistics behave as I would expect, i.e. case 6 is 
not an outlier but cases 13 and 36 are.  As far as I can tell, with Stata's 
logistic regression, the residuals produced by the -deviance-, -rstandard-, 
and -deviance- parameters on -predict- will all be the same for cases that 
have the same values on the covariates, regardless of whether they have the 
same value on the outcome measure.  I imagine there is a logic behind this, 
but I don't know what it is, and it is not the same logic used by SPSS in 
computing residuals.

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