Dear R fans,

I am trying to do step-wise linear regression using the F-test to decide
which variables to admit.  Ewout Steyerberg suggests using the F-test for
this purpose.

I first build a model using no variables using lm(y ~ 1) and then using one
variable that is a strong predictor using lm(y ~ x).  When I call var.test
on these two models, I do not get a significant p-value—0.07.  But a summary
of the second model gives a F-test p-value that is very small.

My questions are:

Should I be using var.test to run the F-test to decide which variable to add
next?

What is the difference between the F-test run by var.test and summary.lm?

Has step-wise model building using the F-test been programmed already?

Thanks!

Troy

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