I am currently trying to run a logit for identifying the probability of being a tribal versus non-tribal on the subsample of adult women only. I have 5 rounds of data and my independent variable includes years of education, age, marital status, rural residence, children under 5, household size, age of household head AND monthly per capita income.
I have also included a set of zone dummies zone1-zone6 which divides the country into 6 unique zone-with each zone consisting of a group of states.
This is the command I use
The issue I run into is that for rounds 1,2 and 3 the logit converges perfectly, however for rounds 4 and 5, after about 6 iterations, the model starts saying (backed up) like this
I tried introducing the variables sequentially and it seems the monthly per capita income (n_mpce) is the problem variable. I cannot remove it from my model since it's the only measure of socioeconomic status I have. I tried converting it to daily per capita income to reduce the scale- that doesn't seem to work either.
My question is
1. What does stata mean by (backed up)- how is it different from (not concave) warning.
2. If I restrict the iterations to 100 and broadly get the results I want (for reweighting)- how big of an issue is this non-convergence of the model.
3. Why is the non-convergence happening in round 4 and 5 only and not in the earlier rounds- the unit of measurement of MPCE has been same in all rounds.
I have also included a set of zone dummies zone1-zone6 which divides the country into 6 unique zone-with each zone consisting of a group of states.
This is the command I use
Code:
foreach r in 1 2 3 4 5 { logit scst age yrs_ed rural marital n_mpce ch_under5 fhead headage heademp hhsize i.zone [aw=hhwt] /* */ if (keep_ageRC==1) & (sex==2) & (round==`r'), iterate (100) predict phatscst`r' if e(sample), pr sum scst [aw=hhwt] if (keep_ageRC==1) & (sex==2) & (round==`r') gen pbarscst`r'=r(mean) gen scstwt`r'= (phatscst`r'/(1-phatscst`r')) * ((1-pbarscst`r')/ pbarscst`r') * (hhwt) if scst==0 & round==`r' }
Code:
Iteration 0: log pseudolikelihood = -1.683e+08 Iteration 1: log pseudolikelihood = -1.557e+08 Iteration 2: log pseudolikelihood = -1.545e+08 Iteration 3: log pseudolikelihood = -1.545e+08 Iteration 4: log pseudolikelihood = -1.545e+08 (backed up) Iteration 5: log pseudolikelihood = -1.545e+08 (backed up) Iteration 6: log pseudolikelihood = -1.545e+08 (backed up) Iteration 7: log pseudolikelihood = -1.545e+08 (backed up) Iteration 8: log pseudolikelihood = -1.545e+08 (backed up) Iteration 9: log pseudolikelihood = -1.545e+08 (backed up) Iteration 10: log pseudolikelihood = -1.545e+08 (backed up) . . .<output omitted> Warning: Convergence not achieved
My question is
1. What does stata mean by (backed up)- how is it different from (not concave) warning.
2. If I restrict the iterations to 100 and broadly get the results I want (for reweighting)- how big of an issue is this non-convergence of the model.
3. Why is the non-convergence happening in round 4 and 5 only and not in the earlier rounds- the unit of measurement of MPCE has been same in all rounds.
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