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
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