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* Example generated by -dataex-. For more info, type help dataex clear input float(study_id red yellow green) 1 16044 16532 . 2 . . 21254 3 . 19516 19213 4 18359 . 18890 5 . . 18438 6 22042 17578 . 7 . . 20036 8 . 20179 . 9 . . 15718 10 18874 22474 19873 end format %td red format %td yellow format %td green
date1 and color1 will be the date and corresponding variable name (color) for one of the date values here. There should be no missing values for these 2 new variables because every row has at least 1 date in it.
date2 and color2 will be the date and corresponding variable name (color) for the second date value, for those who have one. Those individuals who only had 1 date value (n=4)will be have missing values for these 2 new variables.
date3 and color3 will be the date and corresponding variable name (color) for the third date value, for those who have it. Only 1 individual has 3 dates so this variable will have 9 missing values.
Chronological order doesn't really matter, because I'm going to eventually reshape it to long anyway. So I don't care if date1 is the earliest date or date3 is earliest or if it's in some random order.
I have no idea how to do this so any help would be much appreciated.
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