risking to be slaughtered on SAS-L, let me give you a scenario where I
think stepwise regression could be used.
1. You are trying to predict something.
2. You have a lot of independent variables and the selection of
variables presents a problem for you.
3. You have enough data points to split your data into a large enough
training data set (where you build the model) and a large enough test
or validation data set where you can select the best model.
4. You build a number of competing models, one of which is created with
5. If on the set aside test data set stepwise regression gives you the
best predictions, select this model.
Do I think it's realistic to expect stepwise regression can produce the
best model? Yes, it can. Would you prefer a model that is theoretically
sound or the one that gives you better predictions? I'd prefer the
latter if prediction were my sole goal.
My 2 cents,
Michael Ni wrote:
> I know that stepwise regression has some shortcomings though it has been
> still widely used in different industries. So my question is that when
> would be a good time to use stepwise regression? In what scenario?