Logistic regression | Number of obs = 266 | |||||
LR chi2(6) = 30.80 | ||||||
Prob > chi2 = 0.0000 | ||||||
Pseudo R2 = 0.0985 | ||||||
Log likelihood = -140.90484 | ||||||
| Odds Ratio | Std. Err. | z | P > |z| | [95% Conf. Interval] | |
Q 11 | 1.871914 | 0.560703 | 2.09 | 0.036 | 1.040691 | 3.367055 |
Q 25 | 0.9850502 | 0.0056331 | −2.63 | 0.008 | 0.9740712 | 0.9961528 |
Q 17 | 0.95293 | 0.0215055 | −2.14 | 0.033 | 0.9116986 | 0.996026 |
Q 22 & 11 | 2.443402 | 0.8058512 | 2.71 | 0.007 | 1.280155 | 4.663663 |
Q 22 & 12 | 4.019569 | 4.818084 | 1.16 | 0.246 | 0.3836021 | 42.11899 |
Q 22 & 13 | 0.0797545 | 0.0958384 | −2.10 | 0.035 | 0.0075665 | 0.8406524 |