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

From: Biedermann, Jürgen <juergen.biedermann_at_charite.de>
Date: Fri, 29 Apr 2011 17:29:40 +0100


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
Jürgen



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