R help - Aug 2001 - Missing values in glm

Dear r-help

I am trying to fit a logistic regression with a dataset that has some 
missing values in the categorical response (sjukdom). These are generated 
'false' values that I want predicited values for.

Looking at the help, I think the correct commands to deal with these missing 
values are as follows:

options(na.action=napredict)
my.dum<-glm(sjukdom~as.factor(sex)+age+log.nrg+five.d+five2+five3+d1+d2+d3+d4+d5,na.action,family="binomial")

However, I get the following error message:
'Error in as.data.frame.default(data) : can't coerce function into a 
data.frame'

I have not been able to come up with anything better as other things treat 
the variable sjukdom as a different length and so will not do the regression 
either.

Could you let me know how to solve this please?

Many thanks

Rebecca Deacon
Post-Grad Statistics Student


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On 25-Aug-2001 Becki Deacon wrote:
> Dear r-help
> 
> I am trying to fit a logistic regression with a dataset that has some 
> missing values in the categorical response (sjukdom). These are generated 
> 'false' values that I want predicited values for.
To predict new response values from a fitted model, use predict() function.
This is a generic function that has a method for glm. See the help
pages for "predict" and "predict.glm".

Martyn
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