Hui Du <Hui.Du <at> dataventures.com> writes: > I know in R there is function named 'step', which does the > stepwise regression and choose the model by AIC. > However, if I want to choose a model per this logic: > > 1. Run a full model (linear regression, f = lm(y ~., data = ZZZ), > for example) > > 2. Pick up the variable with biggest p value, delete it from the module and get a new regression model. > > 3. Repeat step 2 until all variables are significant in a model. > > My question is that do you know if R has a function (like 'step') > to do that or I must write it by myself?
There is a fastbw function in the rms package that will do something like this. However, I'm now going to SHOUT AT YOU A LITTLE BIT (sorry). THERE ARE VERY, VERY FEW SITUATIONS WHERE STEPWISE REGRESSION BASED ON P-VALUES MAKES SENSE. IF YOU'RE PLANNING TO USE THIS IN A REAL STATISTICAL SETTING, PLEASE GOOGLE "stepwise regression bad", READ SOME OF THE ENSUING LINKS, AND REEVALUATE YOUR PLANS. We now return you to your regular programming, and remind you that all advice from r-help comes with a 100% money-back guarantee ... Ben Bolker ______________________________________________ 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.
