Hello,    Suppose I have a dataset containing input variables like this:   (Binary)            (Interval)         (Binary) HaveAChild      AgeOfChild     ChildIsMarried 1                      12                   1 0                       .                     . 0                       .                     . 1                      20                   0 1                      11                   1 0                       .                     .   In my predictive modelling, I would like to make use of models such as regression or neural networks, which require complete cases.   However, the AgeOfChild and ChildIsMarried variables are missing for observations where HaveAChild=0, which is expected since there is no child to begin with.   In this case, how can I handle these missing values without discarding them, considering that imputation wouldn't really make sense (e.g. not having a child but having a child age).   Thank you.      ... View more