R help - Oct 2004 - Using model operator in stepwise function's upper scope formula

Hello:

I am doing forward stepwise analysis on the glm model. I am trying to use model 
operator in the "upper" scope formula, for example,          

                       scope=list(lower=~1,upper=~ .^2)

but the upper bound of the scope seems to be ignored and add1 is not performed 
at all, while if the terms are explicitly listed in the formula, the step 
function seems to work properly. Example:
> version 
platform sparc-sun-solaris2.9
arch     sparc               
os       solaris2.9          
system   sparc, solaris2.9   
status                       
major    1                   
minor    9.0                 
year     2004                
month    04                  
day      12                  
language R                   
> testdata
      effect  fa1 fa2    fa3
1  0.5054526 -1.4   1 -15.42
2  0.1366526 -2.5   3 -14.72
3  0.4798526 -1.1   3 -16.43
4  0.5566526 -4.6   2 -17.62
5  0.6568526 -3.5   7  -5.41
6  0.6653526  0.0   5 -11.88
7  0.6376526  0.0   5 -11.72
8  0.5203526 -2.9  -1 -14.72
9  0.4905526 -2.1   2 -17.68
10 0.6376526 -1.1   1 -13.39
> step (glm(effect ~ 1 , data=testdata), scope=list(lower=~1,upper=~.), 
direction='forward')
Start:  AIC= -5.89 
 effect ~ 1 


Call:  glm(formula = effect ~ 1, data = testdata) 

Coefficients:
(Intercept)  
     0.5287  

Degrees of Freedom: 9 Total (i.e. Null);  9 Residual
Null Deviance:      0.2178 
Residual Deviance: 0.2178       AIC: -5.89 

===============================================================
But if I listed the term explicitly in the formula, then step function seemed to
work correctly:
> step (glm(effect ~ 1 , data=testdata), 
scope=list(lower=~1,upper=~fa1+fa2+fa3), direction='forward')
Start:  AIC= -5.89 
 effect ~ 1 

       Df Deviance     AIC
+ fa3   1   0.1778 -5.9188
<none>      0.2178 -5.8901
+ fa2   1   0.2023 -4.6271
+ fa1   1   0.2065 -4.4194

Step:  AIC= -5.92 
 effect ~ fa3 

       Df Deviance     AIC
<none>      0.1778 -5.9188
+ fa1   1   0.1698 -4.3783
+ fa2   1   0.1770 -3.9605

Call:  glm(formula = effect ~ fa3, data = testdata) 

Coefficients:
(Intercept)          fa3  
    0.78310      0.01830  

Degrees of Freedom: 9 Total (i.e. Null);  8 Residual
Null Deviance:      0.2178 
Residual Deviance: 0.1778       AIC: -5.919 
===============================================================
I've lookup the online manual of step function but couldn't find a
solution.
Thanks in advance,

Yu Shao
Wadsworth Center, New York State Department of Health,
Albany, NY 12208

`.' means `what is already there'.  In your case, .^2 is 1^2 which is 1,
so it behaves correctly.

Only in a *fit* involving a *data* argument does `.' mean `the rest of the 
variables'.

On Mon, 4 Oct 2004, Yu Shao wrote:
> Hello:
> 
> I am doing forward stepwise analysis on the glm model. I am trying to use
model
> operator in the "upper" scope formula, for example,          
> 
>                        scope=list(lower=~1,upper=~ .^2)
> 
> but the upper bound of the scope seems to be ignored and add1 is not
performed
> at all, while if the terms are explicitly listed in the formula, the step 
> function seems to work properly. Example:
> 
> > version 
> platform sparc-sun-solaris2.9
> arch     sparc               
> os       solaris2.9          
> system   sparc, solaris2.9   
> status                       
> major    1                   
> minor    9.0                 
> year     2004                
> month    04                  
> day      12                  
> language R                   
> 
> > testdata
>       effect  fa1 fa2    fa3
> 1  0.5054526 -1.4   1 -15.42
> 2  0.1366526 -2.5   3 -14.72
> 3  0.4798526 -1.1   3 -16.43
> 4  0.5566526 -4.6   2 -17.62
> 5  0.6568526 -3.5   7  -5.41
> 6  0.6653526  0.0   5 -11.88
> 7  0.6376526  0.0   5 -11.72
> 8  0.5203526 -2.9  -1 -14.72
> 9  0.4905526 -2.1   2 -17.68
> 10 0.6376526 -1.1   1 -13.39
> 
> > step (glm(effect ~ 1 , data=testdata), scope=list(lower=~1,upper=~.), 
> direction='forward')
> Start:  AIC= -5.89 
>  effect ~ 1 
> 
> 
> Call:  glm(formula = effect ~ 1, data = testdata) 
> 
> Coefficients:
> (Intercept)  
>      0.5287  
> 
> Degrees of Freedom: 9 Total (i.e. Null);  9 Residual
> Null Deviance:      0.2178 
> Residual Deviance: 0.2178       AIC: -5.89 
> 
> ===============================================================> 
> But if I listed the term explicitly in the formula, then step function
seemed to
> work correctly:
> 
> > step (glm(effect ~ 1 , data=testdata), 
> scope=list(lower=~1,upper=~fa1+fa2+fa3), direction='forward')
> Start:  AIC= -5.89 
>  effect ~ 1 
> 
>        Df Deviance     AIC
> + fa3   1   0.1778 -5.9188
> <none>      0.2178 -5.8901
> + fa2   1   0.2023 -4.6271
> + fa1   1   0.2065 -4.4194
> 
> Step:  AIC= -5.92 
>  effect ~ fa3 
> 
>        Df Deviance     AIC
> <none>      0.1778 -5.9188
> + fa1   1   0.1698 -4.3783
> + fa2   1   0.1770 -3.9605
> 
> Call:  glm(formula = effect ~ fa3, data = testdata) 
> 
> Coefficients:
> (Intercept)          fa3  
>     0.78310      0.01830  
> 
> Degrees of Freedom: 9 Total (i.e. Null);  8 Residual
> Null Deviance:      0.2178 
> Residual Deviance: 0.1778       AIC: -5.919 
> ===============================================================> 
> I've lookup the online manual of step function but couldn't find a
solution.
> Thanks in advance,
> 
> Yu Shao
> Wadsworth Center, New York State Department of Health,
> Albany, NY 12208
> 
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> 
> 
-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595