A logistic regression model is estimated to analyze the probability of complications for male patients resulting from
Question:
A logistic regression model is estimated to analyze the probability of complications for male patients resulting from a serious infection. Predictor variables include the patient’s weight and age and whether he is diabetic (Diabetes equals 1 if diabetic, 0 otherwise). The accompanying data file includes information on 260 male patients who had tested positive for a serious infection.
a. Estimate the logistic regression model to find the odds of complications for a 60-year-old diabetic patient with a weight of 180 pounds.
b. Find the corresponding odds if the patient is not diabetic.
c. What is the percentage difference in the odds for a diabetic patient compared to a nondiabetic patient, holding the other variables constant?
Patient | Complication | Weight | Age | Diabetes |
1 | 0 | 146 | 50 | 0 |
2 | 0 | 205 | 29 | 0 |
3 | 1 | 215 | 69 | 0 |
4 | 0 | 162 | 45 | 0 |
5 | 0 | 154 | 64 | 0 |
6 | 0 | 143 | 69 | 0 |
7 | 0 | 154 | 29 | 0 |
8 | 0 | 191 | 82 | 0 |
9 | 0 | 142 | 30 | 0 |
10 | 0 | 141 | 62 | 0 |
11 | 0 | 171 | 79 | 0 |
12 | 0 | 205 | 33 | 0 |
13 | 0 | 170 | 49 | 0 |
14 | 0 | 170 | 34 | 0 |
15 | 0 | 161 | 83 | 1 |
16 | 0 | 175 | 78 | 0 |
17 | 0 | 177 | 26 | 1 |
18 | 0 | 183 | 84 | 0 |
19 | 0 | 193 | 51 | 1 |
20 | 0 | 149 | 31 | 1 |
21 | 0 | 157 | 71 | 0 |
22 | 0 | 203 | 40 | 0 |
23 | 0 | 148 | 62 | 0 |
24 | 0 | 197 | 40 | 0 |
25 | 0 | 157 | 38 | 0 |
26 | 0 | 161 | 25 | 0 |
27 | 0 | 180 | 76 | 0 |
28 | 0 | 155 | 78 | 0 |
29 | 0 | 175 | 47 | 0 |
Step by Step Answer:
Business Analytics
ISBN: 9781265897109
2nd Edition
Authors: Sanjiv Jaggia, Alison Kelly, Kevin Lertwachara, Leida Chen