Please let me know if this is possible do in a loop without having to subset manually.
Thank you!
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input byte student_id str6(income sex semester) float math_score 1 "low" "male" "summer" 75.79707 2 "low" "male" "winter" 78.42905 3 "low" "male" "fall" 77.19025 4 "low" "male" "summer" 86.13298 5 "low" "male" "winter" 84.81785 6 "low" "male" "fall" 72.808044 7 "low" "male" "summer" 60.94741 8 "low" "male" "winter" 93.07262 9 "low" "male" "fall" 96.72986 10 "low" "male" "summer" 95.45274 11 "low" "male" "winter" 73.21725 12 "low" "male" "fall" 68.09888 13 "low" "male" "summer" 54.45422 14 "low" "male" "winter" 70.273636 15 "low" "male" "fall" 63.7756 16 "low" "male" "summer" 73.78484 17 "low" "male" "winter" 74.67471 18 "low" "male" "fall" 74.49361 19 "low" "male" "summer" 65.32313 20 "low" "male" "winter" 71.98983 21 "low" "male" "fall" 70.34425 22 "low" "male" "summer" 63.78717 23 "low" "male" "winter" 79.24786 24 "low" "male" "fall" 82.9422 25 "low" "male" "summer" 66.953354 26 "low" "male" "winter" 83.132 27 "low" "male" "fall" 45.36668 28 "low" "male" "summer" 81.48463 29 "low" "male" "winter" 85.73037 30 "low" "male" "fall" 79.11235 31 "low" "male" "summer" 81.41333 32 "low" "male" "winter" 82.6655 33 "low" "male" "fall" 62.9081 1 "low" "male" "summer" 61.16171 2 "low" "male" "winter" 55.96095 3 "low" "male" "fall" 65.61567 4 "low" "male" "summer" 57.84998 5 "low" "male" "winter" 62.85389 6 "low" "male" "fall" 86.14867 7 "low" "male" "summer" 65.382805 8 "low" "male" "winter" 78.90556 9 "low" "male" "fall" 77.81376 10 "low" "male" "summer" 73.22633 11 "low" "male" "winter" 78.89809 12 "low" "male" "fall" 67.75861 13 "low" "male" "summer" 63.12998 14 "low" "male" "winter" 64.939606 15 "low" "male" "fall" 68.52872 16 "low" "male" "summer" 82.71146 17 "middle" "male" "winter" 89.11002 18 "middle" "male" "fall" 52.11129 19 "middle" "male" "summer" 65.83049 20 "middle" "male" "winter" 68.84013 21 "middle" "male" "fall" 69.065605 22 "middle" "male" "summer" 74.18057 23 "middle" "male" "winter" 82.78862 24 "middle" "male" "fall" 67.25807 25 "middle" "male" "summer" 69.853386 26 "middle" "male" "winter" 91.95356 27 "middle" "male" "fall" 76.73396 28 "middle" "male" "summer" 60.11725 29 "middle" "male" "winter" 76.10474 30 "middle" "female" "fall" 70.36514 31 "middle" "female" "summer" 67.02353 32 "middle" "female" "winter" 59.18249 33 "middle" "female" "fall" 79.9767 1 "middle" "female" "summer" 79.48432 2 "middle" "female" "winter" 64.14967 3 "middle" "female" "fall" 84.50146 4 "middle" "female" "summer" 63.50959 5 "middle" "female" "winter" 73.36041 6 "middle" "female" "fall" 81.75935 7 "middle" "female" "summer" 71.10308 8 "middle" "female" "winter" 56.25582 9 "middle" "female" "fall" 77.83181 10 "middle" "female" "summer" 60.94855 11 "middle" "female" "winter" 78.57565 12 "middle" "female" "fall" 83.1645 13 "middle" "female" "summer" 79.3857 14 "high" "female" "winter" 74.47901 15 "high" "female" "fall" 56.33062 16 "high" "female" "summer" 66.48232 17 "high" "female" "winter" 63.08831 18 "high" "female" "fall" 60.62999 19 "high" "female" "summer" 76.90691 20 "high" "female" "winter" 69.44049 21 "high" "female" "fall" 56.89666 22 "high" "female" "summer" 79.77268 23 "high" "female" "winter" 68.887505 24 "high" "female" "fall" 71.54644 25 "high" "female" "summer" 65.84627 26 "high" "female" "winter" 77.20901 27 "high" "female" "fall" 66.96027 28 "high" "female" "summer" 67.319885 29 "high" "female" "winter" 74.991455 30 "high" "female" "fall" 70.49643 31 "high" "female" "summer" 71.18354 32 "high" "female" "winter" 56.2911 33 "high" "female" "fall" 69.46329 end
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