[R] logistic regression in an incomplete dataset

[Desmond Campbell]

Dear all,

I want to do a logistic regression.
So far I've only found out how to do that in R, in a dataset of complete 
cases.
I'd like to do logistic regression via max likelihood, using all the 
study cases (complete and incomplete). Can you help?

I'm using glm() with family=binomial(logit).
If any covariate in a study case is missing then the study case is 
dropped, i.e. it is doing a complete cases analysis.
As a lot of study cases are being dropped, I'd rather it did maximum 
likelihood using all the study cases.
I tried setting glm()'s na.action to NULL, but then it complained about 
NA's present in the study cases.
I've about 1000 unmatched study cases and less than 10 covariates so 
could use unconditional ML estimation (as opposed to conditional ML 
estimation).

regards
Desmond

-- 
Desmond Campbell
UCL Genetics Institute
D.Campbell at ucl.ac.uk
Tel. ext. 020 31084006, int. 54006