|
Marginal Logistic Regression Model for Obesity |
|
Muscatine Coronary Risk Factor Study |
|
The GENMOD Procedure |
|
Model Information |
|
|
Data Set |
WORK.OBESITY |
|
Distribution |
Binomial |
|
Link Function |
Logit |
|
Dependent Variable |
y |
|
Observations Used |
9856 |
|
Missing Values |
4712 |
|
Class Level Information |
||
|
Class |
Levels |
Values |
|
id |
4856 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 ... |
|
occasion |
3 |
1 2 3 |
|
Response Profile |
||
|
Ordered |
y |
Total |
|
1 |
1 |
2112 |
|
2 |
0 |
7744 |
|
PROC GENMOD is modeling the probability that y='1'. |
|
Parameter Information |
|
|
Parameter |
Effect |
|
Prm1 |
Intercept |
|
Prm2 |
gender |
|
Prm3 |
cage |
|
Prm4 |
cage2 |
|
Criteria For Assessing Goodness Of Fit |
|||
|
Criterion |
DF |
Value |
Value/DF |
|
Deviance |
9852 |
10186.1832 |
1.0339 |
|
Scaled Deviance |
9852 |
10186.1832 |
1.0339 |
|
Pearson Chi-Square |
9852 |
9848.5977 |
0.9997 |
|
Scaled Pearson X2 |
9852 |
9848.5977 |
0.9997 |
|
Log Likelihood |
|
-5093.0916 |
|
|
Algorithm converged. |
|
Analysis Of Initial Parameter Estimates |
|||||||
|
Parameter |
DF |
Estimate |
Standard Error |
Wald 95% Confidence Limits |
Chi-Square |
Pr > ChiSq |
|
|
Intercept |
1 |
-1.2275 |
0.0410 |
-1.3078 |
-1.1472 |
897.53 |
<.0001 |
|
gender |
1 |
0.1246 |
0.0492 |
0.0281 |
0.2211 |
6.41 |
0.0114 |
|
cage |
1 |
0.0303 |
0.0089 |
0.0128 |
0.0477 |
11.58 |
0.0007 |
|
cage2 |
1 |
-0.0164 |
0.0027 |
-0.0218 |
-0.0111 |
36.25 |
<.0001 |
|
Scale |
0 |
1.0000 |
0.0000 |
1.0000 |
1.0000 |
|
|
|
|
GEE Model Information |
|
|
Log Odds Ratio Structure |
Fully Parameterized Clusters |
|
Within-Subject Effect |
occasion (3 levels) |
|
Subject Effect |
id (4856 levels) |
|
Number of Clusters |
4856 |
|
Clusters With Missing Values |
3086 |
|
Correlation Matrix Dimension |
3 |
|
Maximum Cluster Size |
3 |
|
Minimum Cluster Size |
1 |
|
Log Odds Ratio Parameter Information |
|
|
Parameter |
Group |
|
Alpha1 |
(1, 2) |
|
Alpha2 |
(1, 3) |
|
Alpha3 |
(2, 3) |
|
Algorithm converged. |
|
Analysis Of GEE Parameter Estimates |
||||||
|
Empirical Standard Error Estimates |
||||||
|
Parameter |
Estimate |
Standard Error |
95% Confidence Limits |
Z |
Pr > |Z| |
|
|
Intercept |
-1.2283 |
0.0477 |
-1.3218 |
-1.1348 |
-25.75 |
<.0001 |
|
gender |
0.1449 |
0.0627 |
0.0221 |
0.2678 |
2.31 |
0.0208 |
|
cage |
0.0418 |
0.0091 |
0.0240 |
0.0596 |
4.60 |
<.0001 |
|
cage2 |
-0.0155 |
0.0023 |
-0.0200 |
-0.0110 |
-6.73 |
<.0001 |
|
Alpha1 |
3.1496 |
0.1280 |
2.8987 |
3.4004 |
24.61 |
<.0001 |
|
Alpha2 |
2.5931 |
0.1352 |
2.3281 |
2.8582 |
19.17 |
<.0001 |
|
Alpha3 |
2.9878 |
0.1236 |
2.7456 |
3.2300 |
24.18 |
<.0001 |
|
Wald Statistics For Type 3 GEE Analysis |
|||
|
Source |
DF |
Chi-Square |
Pr > ChiSq |
|
gender |
1 |
5.35 |
0.0208 |
|
cage |
1 |
21.13 |
<.0001 |
|
cage2 |
1 |
45.25 |
<.0001 |