The SAS System 1 21:28 Wednesday, May 11, 2005 The GENMOD Procedure Model Information Data Set WORK.HIVNET Distribution Binomial Link Function Logit Dependent Variable y Observations Used 3000 Class Level Information Class Levels Values id 1000 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 ... riskgp 4 1 2 3 4 Response Profile Ordered Total Value y Frequency 1 1 1775 2 0 1225 PROC GENMOD is modeling the probability that y='1'. Parameter Information Parameter Effect Prm1 Intercept Prm2 ICgroup Prm3 post Prm4 month12 Prm5 ICgroup*post Prm6 ICgroup*month12 Criteria For Assessing Goodness Of Fit Criterion DF Value Value/DF Deviance 2994 4039.6091 1.3492 Scaled Deviance 2994 4039.6091 1.3492 Pearson Chi-Square 2994 3000.0000 1.0020 Scaled Pearson X2 2994 3000.0000 1.0020 Log Likelihood -2019.8046 The SAS System 2 21:28 Wednesday, May 11, 2005 The GENMOD Procedure Algorithm converged. Analysis Of Initial Parameter Estimates Standard Wald 95% Chi- Parameter DF Estimate Error Confidence Limits Square Pr > ChiSq Intercept 1 0.2574 0.0902 0.0807 0.4342 8.15 0.0043 ICgroup 1 0.0163 0.1276 -0.2338 0.2664 0.02 0.8985 post 1 -0.0648 0.1273 -0.3143 0.1847 0.26 0.6107 month12 1 0.1466 0.1277 -0.1037 0.3969 1.32 0.2509 ICgroup*post 1 0.3665 0.1818 0.0102 0.7227 4.07 0.0438 ICgroup*month12 1 -0.1205 0.1837 -0.4805 0.2395 0.43 0.5118 Scale 0 1.0000 0.0000 1.0000 1.0000 NOTE: The scale parameter was held fixed. GEE Model Information Correlation Structure Unstructured Subject Effect id (1000 levels) Number of Clusters 1000 Correlation Matrix Dimension 3 Maximum Cluster Size 3 Minimum Cluster Size 3 Algorithm converged. Working Correlation Matrix Col1 Col2 Col3 Row1 1.0000 0.3711 0.2751 Row2 0.3711 1.0000 0.3918 Row3 0.2751 0.3918 1.0000 Analysis Of GEE Parameter Estimates Empirical Standard Error Estimates Standard 95% Confidence Parameter Estimate Error Limits Z Pr > |Z| Intercept 0.2574 0.0902 0.0807 0.4342 2.85 0.0043 ICgroup 0.0163 0.1276 -0.2338 0.2664 0.13 0.8985 post -0.0648 0.0985 -0.2580 0.1283 -0.66 0.5107 month12 0.1466 0.1036 -0.0564 0.3496 1.42 0.1568 ICgroup*post 0.3665 0.1444 0.0835 0.6495 2.54 0.0111 ICgroup*month12 -0.1205 0.1432 -0.4012 0.1603 -0.84 0.4003 The SAS System 3 21:28 Wednesday, May 11, 2005 The NLMIXED Procedure Specifications Data Set WORK.HIVNET Dependent Variable y Distribution for Dependent Variable Binomial Random Effects a Distribution for Random Effects Normal Subject Variable id Optimization Technique Dual Quasi-Newton Integration Method Adaptive Gaussian Quadrature Dimensions Observations Used 3000 Observations Not Used 0 Total Observations 3000 Subjects 1000 Max Obs Per Subject 3 Parameters 7 Quadrature Points 20 Parameters B_IC_X_ B_IC_X_ B0 B_ICgroup B_post B_month12 post month12 sigma 0.3 0 0 0 0 0 1 Parameters NegLogLike 1916.68173 Iteration History Iter Calls NegLogLike Diff MaxGrad Slope 1 3 1892.22558 24.45615 78.81191 -1337 2 4 1870.62646 21.59912 11.45786 -578.234 3 6 1869.73699 0.88947 7.582643 -3.15352 4 7 1869.01284 0.724151 4.39984 -3.31256 5 9 1868.65382 0.359024 3.52137 -2.13052 6 11 1868.5722 0.08162 0.466648 -0.18294 7 13 1868.56783 0.004369 0.459775 -0.03191 8 14 1868.5626 0.005226 0.102357 -0.00944 9 16 1868.5625 0.000102 0.006276 -0.00017 10 18 1868.5625 6.567E-7 0.002089 -1.19E-6 The SAS System 4 21:28 Wednesday, May 11, 2005 The NLMIXED Procedure NOTE: GCONV convergence criterion satisfied. Fit Statistics -2 Log Likelihood 3737.1 AIC (smaller is better) 3751.1 AICC (smaller is better) 3751.2 BIC (smaller is better) 3785.5 Parameter Estimates Standard Parameter Estimate Error DF t Value Pr > |t| Alpha Lower B0 0.3979 0.1386 999 2.87 0.0042 0.05 0.1259 B_ICgroup 0.02497 0.1957 999 0.13 0.8985 0.05 -0.3591 B_post -0.09903 0.1574 999 -0.63 0.5293 0.05 -0.4079 B_month12 0.2237 0.1579 999 1.42 0.1568 0.05 -0.08609 B_IC_X_post 0.5618 0.2255 999 2.49 0.0129 0.05 0.1192 B_IC_X_month12 -0.1839 0.2269 999 -0.81 0.4177 0.05 -0.6291 sigma 1.7691 0.1067 999 16.58 <.0001 0.05 1.5596 Parameter Estimates Parameter Upper Gradient B0 0.6699 -0.002 B_ICgroup 0.4090 -0.00126 B_post 0.2098 -0.00209 B_month12 0.5336 -0.00101 B_IC_X_post 1.0044 -0.00111 B_IC_X_month12 0.2613 -0.00064 sigma 1.9785 -0.00009