I would like to ask handling missing data in case control data-set (1:2) matched on age and sex factor. Let's say there are 1000 cases and 2000 controls.
1) I would like to remove the whole matched group which contained missing values in education .
For example, 100 cases had no information about education. So I want to remove all cases and as well their respective controls (200 controls). I have group variables for each case-control set.
2) As shown in below table, sex information are missing for all controls. So how can I replace sex information for each controls which will be same as respective cases?
ID | case | group | education | age | Sex |
1 | 1 | 1 | . | 25 | Male |
2 | 0 | 1 | 1 | 25 | . |
3 | 0 | 1 | 2 | 25 | . |
4 | 1 | 2 | . | 30 | Female |
5 | 0 | 2 | 2 | 30 | . |
6 | 0 | 2 | 1 | 30 | . |
7 | 1 | 3 | . | 40 | Male |
8 | 0 | 3 | 1 | 40 | . |
9 | 0 | 3 | 1 | 40 | . |
2998 | 1 | 1000 | 1 | 35 | Male |
2999 | 0 | 1000 | 2 | 35 | . |
3000 | 0 | 1000 | 1 | 35 | . |
Kind Regards,
Moon Lu
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