Iteration 0: log likelihood = −87.129444

Iteration 1: log likelihood = −60.919341

Iteration 2: log likelihood = −60.036189

Iteration 3: log likelihood = −60.027714

Iteration 4: log likelihood = −60.027711

Logistic regression

Number of obs = 138

LR chi2(12) = 54.20

Prob > chi2 = 0.0000

Log likelihood = −60.027711

Pseudo R2 = 0.3111

Satisfaction

Coef.

Std. Err.

Z

P > |z|

[95% Conf.

Interval]

gender

−0.7041091

0.5049579

−1.39

0.163

−1.693808

0.2855903

age

−0.0779157

0.5479484

−0.14

0.887

−1.151875

0.9960435

residence

0.0390207

0.0368509

1.06

0.290

−0.0332056

0.1112471

understanding

0.173153

0.2903223

0.60

0.551

−0.3958682

0.7421742

education

0.3657477

0.2705502

1.35

0.176

−0.1645209

0.8960163

job

−0.0639429

0.3931309

−0.16

0.871

−0.8344652

0.7065794

insurance

0.5942555

1.207695

0.49

0.623

−1.772784

2.961295

income

0.0004521

0.0004838

0.93

0.350

−0.0004962

0.0014004

community

−1.261027

0.5418181

−2.33

0.020

−2.322971

−0.1990828

disease

1.357208

0.5409311

2.51

0.012

0.2970021

2.417413

payment

0.1579794

0.834384

0.19

0.850

−1.477383

1.793342

trust

1.420884

0.3287442

4.32

0.000

0.7765572

2.065211

_cons

−5.197037

2.0217

−2.57

0.010

−9.159496

−1.234578