Dear All, I am new to R and I would like to do the following:
I want to fit a logistic model with 3 predictors and then perform a stepwise regression to select the best possible model using either the AIC/BIC criterion. I have used the stepAIC function which works fine but using this method only likely candidates are evaluated (i.e. not all the models are fitted). We should have 2^3=8 possible models. So I want to do the following. Write a code in R which will allow me to fit all 8 possible models. So, i guess the first combination will be c(0,0,0) for the 3 predictors, then c(0,0,1) for then next one and so one until 8 models are fitted. I would be really grateful if I could get some advise as to how to write the coding to tell R to fit each of these models in turn and extract the log-likelihood for each one of them so that I will be able to calculated AIC/BIC afterwards. Many thanks for your help, A -- View this message in context: http://n4.nabble.com/stepwise-regression-fitting-all-possible-models-tp1838735p1838735.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
