I have been trying to do postestimation for a ordered probit model for each of my 3 possible outcomes, but I keep getting error messages:
outcome() must either be a value of status,
or #1, #2, ...
outcome 1 not found
outcome() must either be a value of status,
or #1, #2, ...
So, if anyone could help me with this issue, I appreciate it.
And one more question: What is the interpretation for \cut1, cut2, and so.
That's' my code and data:
Code:
* Ordered probit model marginal effects margins, dydx(*) atmeans predict(outcome(1)) margins, dydx(*) atmeans predict(outcome(2)) margins, dydx(*) atmeans predict(outcome(3)) //Ordered probit model predicted probabilities predict p1oprobit, pr outcome(1) predict p2oprobit, pr outcome(2) predict p3oprobit, pr outcome(3) //summarize p1oprobit p2oprobit p2oprobit //tabulate status
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input byte(status boy) float age int income byte govaid float night double(lib sci comp sports tage tagesd twom) float(stu_staff_ratio noatte) double(sroom child element) str4 truancy_status 3 1 15.3 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 65 18 1 1 "high" 3 1 16.3 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 85 25 1 1 "high" 2 1 16.6 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 51 18 1 1 "med" 2 0 16.1 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 164 18 1 1 "med" 3 1 15.8 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 15 25 1 1 "high" 3 0 15.8 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 16 18 1 1 "high" 2 1 15.4 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 87 18 1 1 "med" 3 0 15.5 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 55 25 1 1 "high" 3 0 15.9 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 35 18 1 1 "high" 3 0 16.7 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 65 25 1 1 "high" 3 0 15.9 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 52 18 1 1 "high" 3 0 15.2 800 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 60 18 1 1 "high" 3 1 15.1 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 17 25 1 1 "high" 3 0 15.7 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 44 18 1 1 "high" 3 0 15.8 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 76 18 1 1 "high" 3 0 15.9 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 57 25 1 1 "high" 2 0 17.5 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 203 25 1 1 "med" 3 0 15.2 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 20 25 1 1 "high" 3 0 15.9 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 30 25 1 1 "high" 3 1 15.5 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 88 25 1 1 "high" 3 0 15.9 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 54 25 1 1 "high" 2 1 17.1 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 146 25 1 1 "med" 2 0 17.6 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 72 25 1 1 "med" 2 1 16.3 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 93 18 1 1 "med" 2 0 16.7 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 58 25 1 1 "med" 3 1 15.3 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 36 18 1 1 "high" 2 0 15.9 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 142 25 1 1 "med" 3 1 15.3 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 30 18 1 1 "high" 2 1 16 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 177 25 1 1 "med" 1 1 16.4 700 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 . 18 1 1 "low" 2 1 15.6 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 92 25 1 1 "med" 2 1 17 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 185 25 1 1 "med" 2 1 16.1 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 77 25 1 1 "med" 2 0 15.8 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 63 25 1 1 "med" 3 1 16.1 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 39 18 1 1 "high" 3 0 14.9 . 0 0 1 1 1 0 43.54 10.11 81.08 .8372093 23 25 1 1 "high" 3 0 16.8 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 82 19 1 1 "high" 3 0 17.7 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 57 19 1 1 "high" 3 0 16.9 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 34 19 1 1 "high" 3 0 18.6 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 79 31 1 1 "high" 3 0 15.2 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 21 14 1 1 "high" 3 1 15.1 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 22 31 1 1 "high" 3 1 15.8 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 56 31 1 1 "high" 3 1 15.7 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 65 31 1 1 "high" 3 1 15.9 1000 0 1 1 1 1 0 43.54 10.11 81.08 1.767442 38 17 1 1 "high" 3 0 16.9 . 0 1 1 1 1 0 43.54 10.11 81.08 1.767442 30 3 1 1 "high" 2 0 18.4 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 118 31 1 1 "med" 3 0 15.9 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 18 19 1 1 "high" 3 1 16.8 . 0 1 1 1 1 0 43.54 10.11 81.08 1.767442 8 3 1 1 "high" 3 1 15.8 . 0 0 1 1 1 0 43.54 10.11 81.08 1.767442 24 14 1 1 "high" end
Listed 50 out of 84409 observations
Thank you all,
Max
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