I'm trying to do logistic regression, but I can't seem to get the results I want. I have 6 columns of data (one dependent and 5 independent binary variables) and about 100 rows. The problem with my dataset is that I have a lot of missing ness in the data (NA's) which I think is the reason why I can't do the regression. Is there any way to tackle the situation? I think removing the rows with NA's in them not a good idea because ill have very less data left.
Solved – Handling missing data in logistic regression
logisticmissing datarregressionregression-strategies
Best Answer
Without much more information we can't give you guaranteed advice here.