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Marginal Logistic Regression Model for Obesity |
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Muscatine Coronary Risk Factor Study |
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The GENMOD Procedure |
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Model Information |
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Data Set |
WORK.OBESITY |
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Distribution |
Binomial |
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Link Function |
Logit |
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Dependent Variable |
y |
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Observations Used |
9856 |
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Missing Values |
4712 |
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Class Level Information |
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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 ... |
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occasion |
3 |
1 2 3 |
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Response Profile |
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Ordered |
y |
Total |
|
1 |
1 |
2112 |
|
2 |
0 |
7744 |
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PROC GENMOD is modeling the probability that y='1'. |
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Parameter Information |
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|
Parameter |
Effect |
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Prm1 |
Intercept |
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Prm2 |
gender |
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Prm3 |
cage |
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Prm4 |
cage2 |
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Criteria For Assessing Goodness Of Fit |
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Criterion |
DF |
Value |
Value/DF |
|
Deviance |
9852 |
10186.1832 |
1.0339 |
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Scaled Deviance |
9852 |
10186.1832 |
1.0339 |
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Pearson Chi-Square |
9852 |
9848.5977 |
0.9997 |
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Scaled Pearson X2 |
9852 |
9848.5977 |
0.9997 |
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Log Likelihood |
|
-5093.0916 |
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Algorithm converged. |
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Analysis Of Initial Parameter Estimates |
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Parameter |
DF |
Estimate |
Standard Error |
Wald 95% Confidence Limits |
Chi-Square |
Pr > ChiSq |
|
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Intercept |
1 |
-1.2275 |
0.0410 |
-1.3078 |
-1.1472 |
897.53 |
<.0001 |
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gender |
1 |
0.1246 |
0.0492 |
0.0281 |
0.2211 |
6.41 |
0.0114 |
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cage |
1 |
0.0303 |
0.0089 |
0.0128 |
0.0477 |
11.58 |
0.0007 |
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cage2 |
1 |
-0.0164 |
0.0027 |
-0.0218 |
-0.0111 |
36.25 |
<.0001 |
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Scale |
0 |
1.0000 |
0.0000 |
1.0000 |
1.0000 |
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GEE Model Information |
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Log Odds Ratio Structure |
Replicated Z-Matrix |
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Within-Subject Effect |
occasion (3 levels) |
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Subject Effect |
id (4856 levels) |
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Number of Clusters |
4856 |
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Clusters With Missing Values |
3086 |
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Correlation Matrix Dimension |
3 |
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Maximum Cluster Size |
3 |
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Minimum Cluster Size |
1 |
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Log Odds Ratio Parameter Information |
||
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Cluster Pair |
Alpha1 |
Alpha2 |
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(1, 2) |
1 |
0 |
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(1, 3) |
0 |
1 |
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(2, 3) |
1 |
0 |
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Algorithm converged. |
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Analysis Of GEE Parameter Estimates |
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Empirical Standard Error Estimates |
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Parameter |
Estimate |
Standard Error |
95% Confidence Limits |
Z |
Pr > |Z| |
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Intercept |
-1.2270 |
0.0477 |
-1.3205 |
-1.1335 |
-25.72 |
<.0001 |
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gender |
0.1445 |
0.0627 |
0.0216 |
0.2674 |
2.31 |
0.0212 |
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cage |
0.0416 |
0.0091 |
0.0238 |
0.0594 |
4.58 |
<.0001 |
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cage2 |
-0.0156 |
0.0023 |
-0.0201 |
-0.0111 |
-6.77 |
<.0001 |
|
Alpha1 |
3.0684 |
0.0957 |
2.8809 |
3.2559 |
32.07 |
<.0001 |
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Alpha2 |
2.5929 |
0.1353 |
2.3278 |
2.8581 |
19.17 |
<.0001 |
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Wald Statistics For Type 3 GEE Analysis |
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Source |
DF |
Chi-Square |
Pr > ChiSq |
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gender |
1 |
5.31 |
0.0212 |
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cage |
1 |
20.97 |
<.0001 |
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cage2 |
1 |
45.80 |
<.0001 |