R help - Nov 2011 - help to setting a multiple (linear) regression model with a 5% significance level (threshold) for the inclusion of the model variables.

Dear Researchers,

someone know the right syntax to chose a 5% significance level (threshold)
for the inclusion of the model variables in a  multiple (linear) regression
in backward way?

I set the formula in this way, but I don't know to choose the 5%
significance?

lmodelV <-
step(lm(formula=MyFormula[[1]],data=LR.train),direction="backward")

thanks in advance gianni

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On 22/11/2011 16:30, gianni lavaredo wrote:
> Dear Researchers,
>
> someone know the right syntax to chose a 5% signi???cance level (threshold)
> for the inclusion of the model variables in a  multiple (linear) regression
> in backward way?
>
> I set the formula in this way, but I don't know to choose the 5%
> significance?
>
> lmodelV<-
>
step(lm(formula=MyFormula[[1]],data=LR.train),direction="backward")
That is not what step() does.  Please do read the help page!

Description:

      Select a formula-based model by AIC.

Note, 'by AIC'.

Now, as Frank Harrell says here often, stepwise methods are inadmissible 
for prediction, and in addition stepwise F-test methods are always 
invalid as they ignore multiple testing.  So you won't find such methods 
prominently available in R (and all the stepwise methods I am aware of 
in R packages use AIC or similar).

The author of step()
> thanks in advance gianni
>
> 	[[alternative HTML version deleted]]
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>
>
>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
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