Logistic Regression 

[DataSet3] D:\Saved\WINWORD\MGS9950\fox-data\chile.sav

Case Processing Summary
Unweighted Cases(a)
N Percent
Selected Cases Included in Analysis 1709 97.3
Missing Cases 48 2.7
Total 1757 100.0
Unselected Cases 0 .0
Total 1757 100.0
a If weight is in effect, see classification table for the total number of cases.

Dependent Variable Encoding
Original Value Internal Value
1 0
2 1

Block 0: Beginning Block


Classification Table(a,b)

Observed
Predicted
1=for,2=against Percentage Correct
1 2
Step 0 1=for,2=against 1 0 840 .0
2 0 869 100.0
Overall Percentage

50.8
a Constant is included in the model.
b The cut value is .500

Variables in the Equation


B S.E. Wald df Sig. Exp(B)
Step 0 Constant .034 .048 .492 1 .483 1.035

Variables not in the Equation



Score df Sig.
Step 0 Variables Gender 33.721 1 .000
Age 35.252 1 .000
MOIncomeSTD .059 1 .809
Overall Statistics 70.234 3 .000

Block 1: Method = Enter

Omnibus Tests of Model Coefficients


Chi-square df Sig.
Step 1 Step 71.325 3 .000
Block 71.325 3 .000
Model 71.325 3 .000

Model Summary
Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square
1 2297.360(a) .041 .055
a Estimation terminated at iteration number 3 because parameter estimates changed by less than .001.


Classification Table(a)

Observed
Predicted
1=for,2=against Percentage Correct
1 2
Step 1 1=for,2=against 1 483 357 57.5
2 333 536 61.7
Overall Percentage

59.6
a The cut value is .500

Variables in the Equation


B S.E. Wald df Sig. Exp(B)
Step 1(a) Gender -.590 .099 35.366 1 .000 .555
Age -.020 .003 36.676 1 .000 .980
MOIncomeSTD -.001 .049 .000 1 .986 .999
Constant 1.681 .206 66.369 1 .000 5.371
a Variable(s) entered on step 1: Gender, Age, MOIncomeSTD.

Block 2: Method = Enter

Omnibus Tests of Model Coefficients


Chi-square df Sig.
Step 1 Step 1579.530 1 .000
Block 1579.530 1 .000
Model 1650.855 4 .000

Model Summary
Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square
1 717.830(a) .619 .826
a Estimation terminated at iteration number 6 because parameter estimates changed by less than .001.


Classification Table(a)

Observed
Predicted
1=for,2=against Percentage Correct
1 2
Step 1 1=for,2=against 1 770 70 91.7
2 59 810 93.2
Overall Percentage

92.5
a The cut value is .500

Variables in the Equation


B S.E. Wald df Sig. Exp(B)
Step 1(a) Gender -.620 .201 9.548 1 .002 .538
Age -.009 .007 1.843 1 .175 .991
MOIncomeSTD .266 .103 6.607 1 .010 1.305
StatQuo -3.210 .147 477.172 1 .000 .040
Constant 1.033 .389 7.043 1 .008 2.808
a Variable(s) entered on step 1: StatQuo.

Descriptives 

[DataSet3] D:\Saved\WINWORD\MGS9950\fox-data\chile.sav

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation
1 = male 1757 1 2 1.48 .500
years 1757 18.0 70.0 38.057 14.9547
Support for satus quo 1754 -1.73 1.71 .0040 1.08453
1=for,2=against 1757 1 2 1.51 .500
MOIncomeSTD 1710 -.80 3.81 .0000 1.00000
Valid N (listwise) 1709




Correlations 

[DataSet3] D:\Saved\WINWORD\MGS9950\fox-data\chile.sav

Correlations


1 = male years Support for satus quo 1=for,2=against MOIncomeSTD
1 = male Pearson Correlation 1 -.017 .107(**) -.145(**) -.042
Sig. (2-tailed)
.466 .000 .000 .086
N 1757 1757 1754 1757 1710
years Pearson Correlation -.017 1 .157(**) -.153(**) -.003
Sig. (2-tailed) .466
.000 .000 .896
N 1757 1757 1754 1757 1710
Support for satus quo Pearson Correlation .107(**) .157(**) 1 -.855(**) .035
Sig. (2-tailed) .000 .000
.000 .144
N 1754 1754 1754 1754 1709
1=for,2=against Pearson Correlation -.145(**) -.153(**) -.855(**) 1 .006
Sig. (2-tailed) .000 .000 .000
.796
N 1757 1757 1754 1757 1710
MOIncomeSTD Pearson Correlation -.042 -.003 .035 .006 1
Sig. (2-tailed) .086 .896 .144 .796
N 1710 1710 1709 1710 1710
** Correlation is significant at the 0.01 level (2-tailed).