Following the advice on the previous questions in Statlist, I did my regression model with one, two, (and so on) predictors, and figured out what variable is a trouble maker.
But then, now what? How should I change my model specification?
The age at the first delivery "age_birth" is one of the important independent variables to explain the independent variable of number of the children.
Code:
xtologit children_number age_birth Fitting comparison model: Iteration 0: log likelihood = -8247.2149 Iteration 1: log likelihood = -8123.6735 Iteration 2: log likelihood = -8123.1374 Iteration 3: log likelihood = -8123.1374 Refining starting values: Grid node 0: log likelihood = -5293.4722 Fitting full model: Iteration 0: log likelihood = -5293.4722 Iteration 1: log likelihood = -3482.5691 Iteration 2: log likelihood = -3119.9269 Iteration 3: log likelihood = -2363.2178 Iteration 4: log likelihood = -2190.7194 Iteration 5: log likelihood = -2089.1869 Iteration 6: log likelihood = -2041.1365 Iteration 7: log likelihood = -2017.9951 (not concave) cannot compute an improvement -- discontinuous region encountered r(430);
0 Response to cannot compute an improvement -- discontinuous region encountered
Post a Comment