I?m trying to do a stepwise logistic regression using the step.glm function.
My question is about how to create the formula for my model. I have a large
set of variables to work with (over 100) and want to do a step-forward
regression which starts with a null model, adding one variable at a time
until it attains the best fit.
The problem is, as input to step.glm, I must define the scope of models for
the stepwise search. The formula for the lower bound is easy (it?s RESPONSE
~ 1) but the upper bound should contain all of the more than 100 potential
regressor variables. My question is, how can this be done in Splus without
having to explicitly list every single one of the variables in the formula
(i.e., RESPONSE ~ X1 + X2 + ? + X100 + ?)?
I?ve tried doing this by using a matrix, X, where each column of the matrix
contains one of the regressor variables and then using the formula RESPONSE
~ X. The problem with this is that X is considered a single factor and in
the stepwise regression, only the entire matrix is considered for addition,
not individual columns of the matrix.
I think there must be a simple solution to this problem, but haven't had any
luck looking through the manuals I have. Any help you can give would be
greatly appreciated.
Thanks,
Michael Radmacher
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