[R] Setting constraints in the glm package

[David Winsemius]

On Oct 26, 2010, at 9:27 AM, David Smith wrote:

>
> Many thanks for the help.

You could express your thanks by including context the next time you  
present a follow-up (as requested in the Posting Guide). Only a  
minority of readers view this list on Nabble, so we don't see the web  
delivered sequence.
>
> I assumed that I would need to account for the variables in the  
> model, even
> though I wish to assign a zero coefficient to them. I've looked at the
> offset function, but does this not just assign the value 1 to the  
> variables?
> How would I specify a zero coefficient to more than one predictor in  
> the glm
> model? Do I do this directly somehow  i.e.
> y~I(X1)+offset(X2==0)+offset(X3==0)... ?

No, I assumed you had read and understood Viechtbauer's comment that  
leaving the zero-parameter variables items out of the model would give  
you the correct result. I suppose if you wanted evidence of this show  
up in the output of print.glm you could have tried:

  y ~ X1 + I(X2*0) + I(X3*0)

But I suspect glm would omit the singularly valued column when it was  
setting up the model matrix.

If you were hoping to use offset to constrain a parameter to a non- 
zero value, say 4.5, you would do something like:

offx3 <- 4.5*x3
glm( y ~ x1+x2+ offset(offx3), data= ..... )

-- 
David W.