Can logistic regression provide a predicted value for observations with missing values?
Here are the details:
- I have a file with about 10K rows, about 3K have all complete values for all variables.
- I ran a logistic regression (
glm) to estimate coefficients and significance for each predictor
- Now when I try to predict the probabilities of the dependent variable using the fitted model, I only get values for the 3K rows that all have values for the independent variables
I would like to have some predicted probability for all 10K rows, is that even possible? How do I do that in R? I have tried
na.action=na.exclude/na.pass and that only provides values for the 3K rows.