Hi, On Wed, Jan 27, 2010 at 12:21 PM, <francesca.ior...@googlemail.com> wrote: > Hello everybody, > I would need some help from you. > I am trying to fit a logistic model to some presence absence data of > animals living on river islands. I have got 12 predictor variables and I am > trying to use a stepwise forward method to fit the best logistic model to > my data. I am using the function STEP (stats). > I have a question for you. Can I use step function if my variables have a > binomial distribution? > Reading the explanations of the function, I have understood that step is > more suitable for dealing with gaussian distributed variables. > Is that right? > > I apologize in advance for this question, but I am just at the beginning of > my long path to handle and know statistics and R.
This isn't really answering your question at all, but instead of doing stepwise regression, could I recommend trying a regularized/penalized regression model, instead? The glmnet function in the glmnet package can fit the entire regularization path for lasso/elasticnet -regularized logistic regression model ... might be worth a try. -steve -- Steve Lianoglou Graduate Student: Computational Systems Biology | Memorial Sloan-Kettering Cancer Center | Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact ______________________________________________ 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.