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