Hi,
I plan to create a logistic regression model in SAS, but I am working with categorical data (independent variables) with missing values.
Should I eliminate the missing values before fitting the model? I'm leaning towards this because the goal is not to predict using missing categorical values.
OR
Should I create a new category for missing variables? If I do that, then I'd have to create an extra dummy variable.
Thank you in advance for your help!
SMajid
If you have a big table, you could remove them. OR using PROC MI to populate these missing value.
If you have a big table, you could remove them. OR using PROC MI to populate these missing value.
Do you have random missing or systematic missing?
By default the regression procedures will eliminate any record from analysis with missing values for any variable on the model statement.
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