[R] Define a glm object with user-defined coefficients (logistic regression, family="binomial")

David Winsemius dwinsemius at comcast.net
Sat Nov 13 17:15:09 CET 2010

On Nov 13, 2010, at 7:43 AM, Jürgen Biedermann wrote:

> Hi there,
> I just don't find the solution on the following problem. :(
> Suppose I have a dataframe with two predictor variables (x1,x2) and  
> one depend binary variable (y). How is it possible to define a glm  
> object (family="binomial") with a user defined logistic function  
> like p(y) = exp(a + c1*x1 + c2*x2) where c1,c2 are the coefficents  
> which I define. So I would like to do no fitting of the  
> coefficients. Still, I would like to define a GLM object because I  
> could then easily use other functions which need a glm object as  
> argument (e.g. I could use the anova,

The anova results would have not much interpretability in this  
setting. You would be testing for the Intercept being zero under very  
artificial conditions. You have eliminated much statistical meaning by  
forcing the form of the results.

> summary functions).

# Assume dataframe name is dfrm with variables event, no_event, x1,  
x2, and further assume c1 and c2 are also defined:

dfrm$logoff <- with(dfrm, log(c1*x1 + c2*x2))
forcedfit <- glm( c(event,no_event) ~ 1 + offset(logoff), data=dfrm)

(Obviously untested.)

> Thank you very much! Greetings
> Jürgen
> -- 
> -----------------------------------
> Jürgen Biedermann

David Winsemius, MD
West Hartford, CT

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