I'm comparing plausible models selected a-priori to predict a binary response variable. I used binary logistic regression in SPSS20 and obtained AIC=-2*LogLikelihood+2k where k is the number of parameters in the model. Using the GLM procedure (binary logistic) I get provided with AIC, AICc, BIC etc. straight away, however, the output differs from the binary logistic regression output (and results in different ranking of the models).
Why do the outputs using binary logistic regression vs GLM (binary logistic) differ? And which approach should I use?