The SAS System The Mixed Procedure Model Information Data Set WORK.ONE Dependent Variable y Covariance Structures Variance Components, Autoregressive Subject Effects id(trt), id(trt) Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Containment Class Level Information Class Levels Values id 38 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 trt 2 0 1 timepnt 5 1 2 3 4 5 Dimensions Covariance Parameters 3 Columns in X 18 Columns in Z per Subject 1 Subjects 38 Max Obs per Subject 5 Number of Observations Number of Observations Read 190 Number of Observations Used 190 Number of Observations Not Used 0 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 1060.11349388 1 4 958.10126880 . 2 1 957.66075215 0.00000605 3 1 957.65885102 0.00000000 The SAS System The Mixed Procedure Convergence criteria met. Estimated R Matrix for id(trt) 20 0 Row Col1 Col2 Col3 Col4 Col5 1 17.2094 11.9507 8.2990 5.7630 4.0020 2 11.9507 17.2094 11.9507 8.2990 5.7630 3 8.2990 11.9507 17.2094 11.9507 8.2990 4 5.7630 8.2990 11.9507 17.2094 11.9507 5 4.0020 5.7630 8.2990 11.9507 17.2094 Estimated R Correlation Matrix for id(trt) 20 0 Row Col1 Col2 Col3 Col4 Col5 1 1.0000 0.6944 0.4822 0.3349 0.2325 2 0.6944 1.0000 0.6944 0.4822 0.3349 3 0.4822 0.6944 1.0000 0.6944 0.4822 4 0.3349 0.4822 0.6944 1.0000 0.6944 5 0.2325 0.3349 0.4822 0.6944 1.0000 Covariance Parameter Estimates Cov Parm Subject Estimate Intercept id(trt) 0 AR(1) id(trt) 0.6944 Residual 17.2094 Fit Statistics -2 Res Log Likelihood 957.7 AIC (Smaller is Better) 961.7 AICC (Smaller is Better) 961.7 BIC (Smaller is Better) 964.9 Type 1 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F trt 1 36 0.17 0.6839 timepnt 4 144 26.17 <.0001 trt*timepnt 4 144 0.42 0.7908