logistic regression with glm: cooks distance and dfbetas are different compared to SPSS output

Hi there,

I have the problem, that I'm not able to reproduce the SPSS residual 
statistics (dfbeta and cook's distance) with a simple binary logistic 
regression model obtained in R via the glm-function.

I tried the following:

fit <- glm(y ~ x1 + x2 + x3, data, family=binomial)

cooks.distance(fit)
dfbetas(fit)

When i compare the returned values with the values that I get in SPSS, 
they are different, although the same model is calculated (the 
coefficients are the same etc.)

It seems that different calculation-formulas are used for cooks.distance 
and dfbetas in SPSS compared to R.

Unfortunately I didn't find out, what's the difference in the 
calculation and how I could get R to calculate me the same statistics 
that SPSS uses.
Or is this an unknown SPSS bug?

Greetings
J?rgen