[R] stepwise regression

[John Fox]

Dear Jinsong Zhao,

In proc reg in SAS, selection=stepwise does (modified) forward selection. In
step() in R, the default method is "backward" when the scope argument is
absent. To do (modified) forward selection, you can specify an initial model
with only a constant, and use the scope argument to specify all predictors.
See ?step for details.

It's hard to imagine, however, that it makes much sense to search for a
model with 9 predictors and 7 observations -- you'll just end up with a
model that fits perfectly.

I hope this helps,
 John 

--------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox 
-------------------------------- 

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Jinsong Zhao
> Sent: Thursday, April 27, 2006 7:58 PM
> To: r-help
> Subject: [R] stepwise regression
> 
> Dear all,
> 
> I have encountered a problem when perform stepwise regression. 
> The dataset have more 9 independent variables, but 7 observation.
> 
> In R, before performing stepwise, a lm object should be given.
> fm <- lm(y ~ X1 + X2 + X3 + X11 + X22 + X33 + X12 + X13 + X23)
> 
> However, summary(fm) will give: 
> 
> Residual standard error: NaN on 0 degrees of freedom
> Multiple R-Squared:     1,      Adjusted R-squared:   NaN 
> F-statistic:   NaN on 6 and 0 DF,  p-value: NA 
> 
> In this situation, step() or stepAIC() will not give any 
> useful information.
> 
> I don't know why SAS could deal with this situation:
> PROC REG;
>  MODEL y=X1 X2 X3 X11 X22 X33 X12 X13 X23/SELECTION=STEPWISE; RUN;
> 
> Any help will be really appreciated.
> 
> Wishes,
> 
> Jinsong Zhao
> 
>