[R] logistic regression in an incomplete dataset

[JoAnn Alvarez]

Hello Desmond,

The only way to not drop cases with incomplete data would be some sort 
of imputation for the missing covariates.

JoAnn

Desmond Campbell wrote:
> 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
>
>
>   


-- 
JoAnn Álvarez
Biostatistician
Department of Biostatistics
D-2220 Medical Center North
Vanderbilt University School of Medicine
1161 21st Ave. South 
Nashville, TN 37232-2158  

http://biostat.mc.vanderbilt.edu/JoAnnAlvarez