[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