The GLIMMIX Procedure Model Information Data Set KAZ.LEVEL1 Response Variable posttest Response Distribution Gaussian Link Function Identity Variance Function Default Variance Matrix Not blocked Estimation Technique Restricted Maximum Likelihood Degrees of Freedom Method Kenward-Roger Fixed Effects SE Adjustment Kenward-Roger Class Level Information Class Levels Values schoolID 126 750 841 1791 2156 3516 3664 4692 4888 5460 7528 8564 9084 9208 9232 10757 10994 11894 14337 14353 14945 15276 15888 17061 17126 18661 19417 22590 23156 23386 23422 25106 25353 26193 27223 27649 28179 28657 29586 30241 30460 30947 31615 32211 32219 32572 35532 36177 37646 37886 39911 40209 41922 42745 42926 45966 46887 46916 47120 47428 47847 48032 48155 49399 50684 50880 51518 51809 52221 52947 56619 57826 58437 58440 58687 59052 60857 62112 64504 65759 65835 67146 68691 68845 69305 69775 71155 71278 71627 71692 72308 72573 73542 75666 75786 76857 76999 77152 78173 80016 83234 83249 85693 85715 85725 86006 86283 86416 86710 87009 88326 88328 89794 89928 90919 91940 93282 93314 93902 94304 94518 94998 95212 96873 97530 98292 99300 Number of Observations Read 819 Number of Observations Used 819 Dimensions G-side Cov. Parameters 1 R-side Cov. Parameters 1 Columns in X 3 Columns in Z 126 Subjects (Blocks in V) 1 Max Obs per Subject 819 The SAS System 22:34 Thursday, November 17, 2016 2 The GLIMMIX Procedure Optimization Information Optimization Technique Dual Quasi-Newton Parameters in Optimization 1 Lower Boundaries 1 Upper Boundaries 0 Fixed Effects Profiled Residual Variance Profiled Starting From Data Iteration History Objective Max Iteration Restarts Evaluations Function Change Gradient 0 0 4 5874.1490854 . 0.058087 1 0 6 5874.1490836 0.00000183 0.000103 2 0 1 5874.1490836 0.00000000 0.000103 Convergence criterion (GCONV=1E-8) satisfied. Fit Statistics -2 Res Log Likelihood 5874.15 AIC (smaller is better) 5878.15 AICC (smaller is better) 5878.16 BIC (smaller is better) 5883.82 CAIC (smaller is better) 5885.82 HQIC (smaller is better) 5880.45 Generalized Chi-Square 56561.07 Gener. Chi-Square / DF 69.32 Covariance Parameter Estimates Standard Cov Parm Estimate Error schoolID 11.7131 3.0627 Residual 69.3150 3.6834 Solutions for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 53.0819 0.5212 97.12 101.85 <.0001 black -6.1866 1.2432 522.3 -4.98 <.0001 The SAS System 22:34 Thursday, November 17, 2016 3 The GLIMMIX Procedure Solutions for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| urban 0.6228 1.0744 133.5 0.58 0.5631 Type III Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F black 1 522.3 24.76 <.0001 urban 1 133.5 0.34 0.5631