logistic regression in r

Hi all,

Quick question regarding logistic regression in R. I would like to be able to run a model in "Blocks" (a la SPSS) to see the improvement in fit as I add variables, but I can't seem to find an article explaining how. With linear regression you can make multiple linear models and then compare them with anova(), but I'm wondering what the equivalent method is for logistic models...or if there's a package out there that will help

Something like this ?

Kind of, but these methods involve the models being computed automatically, and by pure fit statistics alone. I'd prefer to be able to specify the model blocks for comparison myself. If using linear regression as an example something like this:

model.1=lm(mpg~cyl, data=mtcars)
model.2=lm(mpg~cyl+disp, data=mtcars)


Think I might have found an answer.

the command compare_performance from {performance} (see) here seems to do the job well. I can specify different models and check the AIC and BIC of both using that

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