Hello Frank,

Thank you for the extension and remarks.
The basic weakness of stepwise regression VS going through all-subsets is
very much agreed upon.  Although from what I gather there is one case where
all subsets will be a problem to implement, that is for very LARGE datasets
- especially in the sense of a lot of explanatory variables, and also with
regards to cases where we have more explanatory variables then data points.
In such cases I wonder if using stepwise regression could be found to be
more realistic to implement then all subsets checks.
Then again, I imagine (although not from real experience) that shrinkage
methods (used with LARS) could be practical in those cases too.



I am looking forward to meeting you on Tuesday and taking your first
tutorial of the day,

With regard,
Tal







On Sat, Jul 4, 2009 at 4:22 PM, Frank E Harrell Jr <f.harrell@vanderbilt.edu
> wrote:

> sed for one variable at a time variable selection. AIC is just a
> restatement of the P-value, and as such, doesn't solve the severe problems
> with stepwise v




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