Example - Logistic
Regression of Osteoporosis (yes=1, no=0)
on Age (in years)
Logistic Regression
Table
Odds 95% CI
Predictor
Coef SE Coef
Z P Ratio
Lower Upper
Constant
-4.353 2.4865 1.75 0.0802
age
0.038 0.0072 5.28 0.0000 1.04 1.02 1.05
Example - Logistic
Regression of Cancer (yes=1, no=0)
on Age (in years) and Smoking (yes=1, no=0)
Logistic Regression
Table
Odds 95% CI
Predictor
Coef SE Coef Z
P Ratio Lower
Upper
Constant
-4.4777 2.7465 1.63 0.1032
age
0.1123 0.0386 2.91 0.0036
1.12 1.04 1.21
smoking
1.1638 0.4537 2.57 0.0103
3.21 1.32 7.79
Log-Likelihood =
-137.18596
Test that all slopes
are zero: G = 18.8479, DF = 2, P-Value = 0.000
Example - Logistic
Regression of Frequent Binge Drinking (yes=1, no=0)
on Gender (males=1, females=0)
|
|
YES |
Total |
|
|
Male |
1630 |
7180 |
|
|
Female |
1684 |
9916 |
|
|
Total |
3314 |
17096 |
|
Logistic Regression
Table
Odds 95% CI
Predictor
Coef SE Coef
Z P Ratio Lower Upper
Constant
-1.58686 0.0267449 -59.33 0.000
gender
0.361639 0.0388452 9.31 0.000
1.44 1.33 1.55