Logistic regression | Number of obs = 3299 | ||||||
LR chi2 (4) = 264.73 | |||||||
Prob > chi2 = 0.000 | |||||||
Log likelihood = -1136.85 | Pseudo R2 = 0.1043 | ||||||
E_insurance | Coef. | Std.Err. | z | P>z | [95% Conf.Interval] | ||
edu | 0.6343611 | 0.0641256 | 9.89 | 0.000 | 0.5086772 | 0.760045 | |
job | 0.4392042 | 0.1173416 | 3.74 | 0.000 | 0.2092188 | 0.6691896 | |
car | 0.6373262 | 0.1152562 | 5.53 | 0.000 | −0.8632242 | −0.4114281 | |
region | 0.2648571 | 0.1166416 | 2.27 | 0.023 | 0.0362438 | 0.4934705 | |
_cons | 2.410228 | 0.264117 | 9.13 | 0.000 | −2.927887 | −1.892568 | |