The SAS System The MEANS Procedure Analysis Variable : score N Mean Variance ----------------------------------- 400 5.5650000 4.3917544 ----------------------------------- The SAS System The MEANS Procedure Analysis Variable : score N brandnum Obs N Mean Variance ---------------------------------------------------------- 1 23 21 6.2380952 3.0904762 2 23 22 6.4545455 3.3073593 3 23 19 5.7894737 3.3976608 4 23 19 4.1578947 5.2514620 5 23 20 5.6000000 2.4631579 6 23 17 4.7647059 5.3161765 7 23 18 5.2777778 4.6830065 8 23 17 5.0588235 4.4338235 9 23 20 6.4000000 5.6210526 10 23 19 4.9473684 5.0526316 11 23 21 6.2380952 5.5904762 12 23 22 5.4090909 2.8246753 13 23 20 5.2000000 3.1157895 14 23 22 5.9545455 3.6645022 15 23 20 5.7500000 4.4078947 16 23 21 3.6666667 3.0333333 17 23 21 6.3333333 6.3333333 18 23 20 5.4000000 3.8315789 19 23 22 6.1363636 3.1709957 20 23 19 6.0526316 2.6081871 ---------------------------------------------------------- The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Diagonal Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Residual Dimensions Covariance Parameters 1 Columns in X 2 Columns in Z 0 Subjects 1 Max Obs Per Subject 460 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Covariance Parameter Estimates Cov Parm Estimate Alpha Lower Upper Residual 4.3646 0.05 3.8165 5.0407 Fit Statistics -2 Res Log Likelihood 1729.3 AIC (smaller is better) 1731.3 AICC (smaller is better) 1731.3 BIC (smaller is better) 1735.3 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 4.6297 0.5122 398 9.04 <.0001 price 0.09871 0.05292 398 1.87 0.0629 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F price 1 398 3.48 0.0629 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Diagonal Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Residual Class Level Information Class Levels Values color 2 1 2 Dimensions Covariance Parameters 1 Columns in X 4 Columns in Z 0 Subjects 1 Max Obs Per Subject 460 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Covariance Parameter Estimates Cov Parm Estimate Alpha Lower Upper Residual 4.3262 0.05 3.7822 4.9972 Fit Statistics -2 Res Log Likelihood 1725.9 AIC (smaller is better) 1727.9 AICC (smaller is better) 1727.9 BIC (smaller is better) 1731.9 Solution for Fixed Effects Standard Effect color Estimate Error DF t Value Pr > |t| Intercept 3.9823 0.5936 397 6.71 <.0001 price 0.1413 0.05635 397 2.51 0.0126 color 1 0.4741 0.2225 397 2.13 0.0337 color 2 0 . . . . Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F price 1 397 6.29 0.0126 color 1 397 4.54 0.0337 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Diagonal Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Residual Class Level Information Class Levels Values color 2 1 2 type 2 1 2 Dimensions Covariance Parameters 1 Columns in X 8 Columns in Z 0 Subjects 1 Max Obs Per Subject 460 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Covariance Parameter Estimates Cov Parm Estimate Alpha Lower Upper Residual 4.3181 0.05 3.7739 4.9897 Fit Statistics -2 Res Log Likelihood 1723.8 AIC (smaller is better) 1725.8 AICC (smaller is better) 1725.8 BIC (smaller is better) 1729.8 Solution for Fixed Effects Standard Effect color type Estimate Error DF t Value Pr > |t| Intercept 2.9468 0.8991 395 3.28 0.0011 price 0.2217 0.07559 395 2.93 0.0036 color 1 1.0234 0.4024 395 2.54 0.0114 color 2 0 . . . . type(color) 1 1 -0.4513 0.3231 395 -1.40 0.1633 type(color) 1 2 0 . . . . type(color) 2 1 0.4592 0.3732 395 1.23 0.2192 type(color) 2 2 0 . . . . Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F price 1 395 8.60 0.0036 color 1 395 6.11 0.0139 type(color) 2 395 1.37 0.2545 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Diagonal Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Residual Class Level Information Class Levels Values color 2 1 2 brandnum 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Dimensions Covariance Parameters 1 Columns in X 24 Columns in Z 0 Subjects 1 Max Obs Per Subject 460 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Covariance Parameter Estimates Cov Parm Estimate Alpha Lower Upper Residual 4.0417 0.05 3.5228 4.6850 Fit Statistics -2 Res Log Likelihood 1644.1 AIC (smaller is better) 1646.1 AICC (smaller is better) 1646.1 BIC (smaller is better) 1650.0 Solution for Fixed Effects Standard Effect color brandnum Estimate Error DF t Value Intercept 3.9840 797230 379 0.00 price 0.1593 61373 379 0.00 color 1 0.4936 306863 379 0.00 color 2 0 . . . brandnum(color) 1 1 0.01035 184118 379 0.00 brandnum(color) 1 2 0.7045 0.6211 379 1.13 brandnum(color) 1 3 -0.5975 245490 379 -0.00 brandnum(color) 1 4 -1.5921 0.6441 379 -2.47 brandnum(color) 1 5 -0.4685 122745 379 -0.00 brandnum(color) 1 11 0.5709 31914 379 0.00 brandnum(color) 1 12 -0.1817 61373 379 -0.00 brandnum(color) 1 13 -0.7093 61373 379 -0.00 brandnum(color) 1 14 0.2045 0.6211 379 0.33 brandnum(color) 1 15 0 . . . brandnum(color) 2 6 -0.4917 306863 379 -0.00 brandnum(color) 2 7 -0.2971 184118 379 -0.00 brandnum(color) 2 8 -0.03831 368236 379 -0.00 brandnum(color) 2 9 0.9844 245490 379 0.00 brandnum(color) 2 10 -0.4683 245490 379 -0.00 brandnum(color) 2 16 -1.7490 245490 379 -0.00 brandnum(color) 2 17 0.7585 184118 379 0.00 brandnum(color) 2 18 -0.4934 61373 379 -0.00 brandnum(color) 2 19 -0.07552 61373 379 -0.00 brandnum(color) 2 20 0 . . . Solution for Fixed Effects Effect color brandnum Pr > |t| Intercept 1.0000 price 1.0000 color 1 1.0000 color 2 . brandnum(color) 1 1 1.0000 brandnum(color) 1 2 0.2574 brandnum(color) 1 3 1.0000 brandnum(color) 1 4 0.0139 brandnum(color) 1 5 1.0000 brandnum(color) 1 11 1.0000 brandnum(color) 1 12 1.0000 brandnum(color) 1 13 1.0000 brandnum(color) 1 14 0.7421 brandnum(color) 1 15 . brandnum(color) 2 6 1.0000 brandnum(color) 2 7 1.0000 brandnum(color) 2 8 1.0000 brandnum(color) 2 9 1.0000 brandnum(color) 2 10 1.0000 brandnum(color) 2 16 1.0000 brandnum(color) 2 17 1.0000 brandnum(color) 2 18 1.0000 brandnum(color) 2 19 1.0000 brandnum(color) 2 20 . Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F price 0 . . . color 1 379 0.00 1.0000 brandnum(color) 18 379 2.55 0.0005 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Diagonal Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Residual Class Level Information Class Levels Values brandnum 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Dimensions Covariance Parameters 1 Columns in X 21 Columns in Z 0 Subjects 1 Max Obs Per Subject 460 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Covariance Parameter Estimates Cov Parm Estimate Alpha Lower Upper Residual 4.0311 0.05 3.5141 4.6718 Fit Statistics -2 Res Log Likelihood 1668.0 AIC (smaller is better) 1670.0 AICC (smaller is better) 1670.0 BIC (smaller is better) 1673.9 Solution for Fixed Effects Standard Effect brandnum Estimate Error DF t Value Pr > |t| Intercept 6.0526 0.4606 380 13.14 <.0001 brandnum 1 0.1855 0.6357 380 0.29 0.7706 brandnum 2 0.4019 0.6288 380 0.64 0.5231 brandnum 3 -0.2632 0.6514 380 -0.40 0.6864 brandnum 4 -1.8947 0.6514 380 -2.91 0.0038 brandnum 5 -0.4526 0.6432 380 -0.70 0.4820 brandnum 6 -1.2879 0.6703 380 -1.92 0.0554 brandnum 7 -0.7749 0.6604 380 -1.17 0.2414 brandnum 8 -0.9938 0.6703 380 -1.48 0.1390 brandnum 9 0.3474 0.6432 380 0.54 0.5895 brandnum 10 -1.1053 0.6514 380 -1.70 0.0906 brandnum 11 0.1855 0.6357 380 0.29 0.7706 brandnum 12 -0.6435 0.6288 380 -1.02 0.3068 brandnum 13 -0.8526 0.6432 380 -1.33 0.1858 brandnum 14 -0.09809 0.6288 380 -0.16 0.8761 brandnum 15 -0.3026 0.6432 380 -0.47 0.6383 brandnum 16 -2.3860 0.6357 380 -3.75 0.0002 brandnum 17 0.2807 0.6357 380 0.44 0.6591 brandnum 18 -0.6526 0.6432 380 -1.01 0.3109 brandnum 19 0.08373 0.6288 380 0.13 0.8941 brandnum 20 0 . . . . Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F brandnum 19 380 2.88 <.0001 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Variance Components Subject Effect rater Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Satterthwaite Class Level Information Class Levels Values rater 23 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Dimensions Covariance Parameters 2 Columns in X 2 Columns in Z Per Subject 1 Subjects 23 Max Obs Per Subject 20 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 1729.28495820 1 3 1705.51226421 0.00000618 2 1 1705.50918891 0.00000001 Convergence criteria met. Covariance Parameter Estimates Cov Parm Subject Estimate Alpha Lower Upper Intercept rater 0.5117 0.05 0.2570 1.4729 Residual 3.8513 0.05 3.3558 4.4660 Fit Statistics -2 Res Log Likelihood 1705.5 AIC (smaller is better) 1709.5 AICC (smaller is better) 1709.5 BIC (smaller is better) 1711.8 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 5.5655 0.1797 23 30.98 <.0001 cprice 0.09854 0.04982 379 1.98 0.0487 Solution for Random Effects Std Err Effect rater Estimate Pred DF t Value Pr > |t| Alpha Intercept 1 0.02506 0.3962 73.8 0.06 0.9497 0.05 Intercept 2 -0.5562 0.3962 73.8 -1.40 0.1645 0.05 Intercept 3 -0.7015 0.3962 73.8 -1.77 0.0807 0.05 Intercept 4 -0.1566 0.3962 73.8 -0.40 0.6938 0.05 Intercept 5 -0.2875 0.4802 47.1 -0.60 0.5523 0.05 Intercept 6 0.2794 0.3962 73.8 0.71 0.4829 0.05 Intercept 7 -0.4180 0.4479 57 -0.93 0.3546 0.05 Intercept 8 -0.00072 0.4577 53.9 -0.00 0.9988 0.05 Intercept 9 -0.5199 0.3962 73.8 -1.31 0.1935 0.05 Intercept 10 0.07583 0.4022 71.9 0.19 0.8510 0.05 Intercept 11 -0.4472 0.3962 73.8 -1.13 0.2626 0.05 Intercept 12 -0.1203 0.3962 73.8 -0.30 0.7623 0.05 Intercept 13 -0.1929 0.3962 73.8 -0.49 0.6277 0.05 Intercept 14 0.5993 0.4388 60 1.37 0.1771 0.05 Intercept 15 0.02908 0.4929 43.6 0.06 0.9532 0.05 Intercept 16 0.4610 0.3962 73.8 1.16 0.2483 0.05 Intercept 17 1.1876 0.3962 73.8 3.00 0.0037 0.05 Intercept 18 1.0569 0.4227 65.3 2.50 0.0149 0.05 Intercept 19 -0.04760 0.3962 73.8 -0.12 0.9047 0.05 Intercept 20 -0.01332 0.4683 50.6 -0.03 0.9774 0.05 Intercept 21 -1.1012 0.3962 73.8 -2.78 0.0069 0.05 Intercept 22 -0.4115 0.4229 65.2 -0.97 0.3341 0.05 Intercept 23 1.2603 0.3962 73.8 3.18 0.0021 0.05 Solution for Random Effects Effect rater Lower Upper Intercept 1 -0.7644 0.8145 Intercept 2 -1.3456 0.2332 Intercept 3 -1.4910 0.08790 Intercept 4 -0.9460 0.6328 Intercept 5 -1.2534 0.6785 Intercept 6 -0.5101 1.0688 Intercept 7 -1.3149 0.4789 Intercept 8 -0.9183 0.9169 Intercept 9 -1.3093 0.2696 Intercept 10 -0.7260 0.8776 Intercept 11 -1.2367 0.3422 Intercept 12 -0.9097 0.6692 Intercept 13 -0.9824 0.5965 Intercept 14 -0.2785 1.4772 Intercept 15 -0.9645 1.0227 Intercept 16 -0.3284 1.2504 Intercept 17 0.3982 1.9770 Intercept 18 0.2128 1.9009 Intercept 19 -0.8370 0.7418 Intercept 20 -0.9536 0.9269 Intercept 21 -1.8906 -0.3117 Intercept 22 -1.2560 0.4330 Intercept 23 0.4708 2.0497 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F cprice 1 379 3.91 0.0487 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Unstructured Subject Effect rater Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Satterthwaite Class Level Information Class Levels Values color 2 1 2 brand 20 Anakena Atlas Peak Barbarana Dragon Barbarana Vina Allarde Bridgman Campo viejo Castillo D Cavino Columbia Crest Dallas Conte Febus Fetzer Flora Springs Maple ridge Montecillo Rabbit Ridge Santa Maria Sobon estates Steel Creek Washington Hills casa lapastolle rater 23 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Dimensions Covariance Parameters 2 Columns in X 4 Columns in Z Per Subject 1 Subjects 23 Max Obs Per Subject 20 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 1725.92907573 1 3 1700.97155599 0.00000414 2 1 1700.96951210 0.00000000 Convergence criteria met. Covariance Parameter Estimates Cov Parm Subject Estimate Alpha Lower Upper UN(1,1) rater 0.5273 0.05 0.2662 1.4987 Residual 3.7987 0.05 3.3092 4.4059 Fit Statistics -2 Res Log Likelihood 1701.0 AIC (smaller is better) 1705.0 AICC (smaller is better) 1705.0 BIC (smaller is better) 1707.2 Null Model Likelihood Ratio Test DF Chi-Square Pr > ChiSq 1 24.96 <.0001 Solution for Fixed Effects Standard Effect color Estimate Error DF t Value Pr > |t| Intercept 5.2986 0.2121 41.6 24.98 <.0001 color 1 0.5105 0.2110 385 2.42 0.0160 color 2 0 . . . . cprice 0.1438 0.05290 378 2.72 0.0069 Solution for Random Effects Std Err Effect rater Estimate Pred DF t Value Pr > |t| Alpha Intercept 1 0.03391 0.3967 76.7 0.09 0.9321 0.05 Intercept 2 -0.5542 0.3967 76.7 -1.40 0.1664 0.05 Intercept 3 -0.7013 0.3967 76.7 -1.77 0.0811 0.05 Intercept 4 -0.1499 0.3967 76.7 -0.38 0.7066 0.05 Intercept 5 -0.4180 0.4846 48.8 -0.86 0.3927 0.05 Intercept 6 0.2912 0.3967 76.7 0.73 0.4651 0.05 Intercept 7 -0.4350 0.4491 59.9 -0.97 0.3366 0.05 Intercept 8 0.05426 0.4595 56.5 0.12 0.9064 0.05 Intercept 9 -0.5175 0.3967 76.7 -1.30 0.1960 0.05 Intercept 10 0.07118 0.4028 74.9 0.18 0.8602 0.05 Intercept 11 -0.4440 0.3967 76.7 -1.12 0.2666 0.05 Intercept 12 -0.1131 0.3967 76.7 -0.29 0.7763 0.05 Intercept 13 -0.1866 0.3967 76.7 -0.47 0.6394 0.05 Intercept 14 0.5640 0.4402 62.8 1.28 0.2049 0.05 Intercept 15 0.03652 0.4948 45.9 0.07 0.9415 0.05 Intercept 16 0.4750 0.3967 76.7 1.20 0.2349 0.05 Intercept 17 1.2102 0.3967 76.7 3.05 0.0031 0.05 Intercept 18 1.1218 0.4240 68.1 2.65 0.0101 0.05 Intercept 19 -0.03961 0.3967 76.7 -0.10 0.9207 0.05 Intercept 20 -0.07730 0.4705 53.1 -0.16 0.8701 0.05 Intercept 21 -1.1056 0.3967 76.7 -2.79 0.0067 0.05 Intercept 22 -0.3997 0.4237 68.2 -0.94 0.3489 0.05 Intercept 23 1.2837 0.3967 76.7 3.24 0.0018 0.05 Solution for Random Effects Effect rater Lower Upper Intercept 1 -0.7561 0.8239 Intercept 2 -1.3442 0.2358 Intercept 3 -1.4913 0.08875 Intercept 4 -0.9399 0.6401 Intercept 5 -1.3920 0.5561 Intercept 6 -0.4988 1.0812 Intercept 7 -1.3333 0.4633 Intercept 8 -0.8661 0.9746 Intercept 9 -1.3075 0.2725 Intercept 10 -0.7312 0.8736 Intercept 11 -1.2340 0.3461 Intercept 12 -0.9031 0.6769 Intercept 13 -0.9767 0.6034 Intercept 14 -0.3158 1.4438 Intercept 15 -0.9596 1.0327 Intercept 16 -0.3150 1.2650 Intercept 17 0.4202 2.0002 Intercept 18 0.2758 1.9678 Intercept 19 -0.8296 0.7504 Intercept 20 -1.0209 0.8663 Intercept 21 -1.8956 -0.3156 Intercept 22 -1.2452 0.4458 Intercept 23 0.4937 2.0737 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F color 1 385 5.85 0.0160 cprice 1 378 7.39 0.0069 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Unstructured Subject Effect rater Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Satterthwaite Class Level Information Class Levels Values color 2 1 2 brand 20 Anakena Atlas Peak Barbarana Dragon Barbarana Vina Allarde Bridgman Campo viejo Castillo D Cavino Columbia Crest Dallas Conte Febus Fetzer Flora Springs Maple ridge Montecillo Rabbit Ridge Santa Maria Sobon estates Steel Creek Washington Hills casa lapastolle rater 23 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Dimensions Covariance Parameters 4 Columns in X 4 Columns in Z Per Subject 2 Subjects 23 Max Obs Per Subject 20 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 1725.92907573 1 2 1686.18902459 0.00010432 2 1 1686.13528836 0.00000173 3 1 1686.13445013 0.00000000 Convergence criteria met. Covariance Parameter Estimates Cov Parm Subject Estimate Alpha Lower Upper UN(1,1) rater 0.4008 0.05 0.1635 2.0569 UN(2,1) rater 0.2060 0.05 -0.3294 0.7413 UN(2,2) rater 1.5056 0.05 0.7690 4.1661 Residual 3.4736 0.05 3.0126 4.0499 Fit Statistics -2 Res Log Likelihood 1686.1 AIC (smaller is better) 1694.1 AICC (smaller is better) 1694.2 BIC (smaller is better) 1698.7 Null Model Likelihood Ratio Test DF Chi-Square Pr > ChiSq 3 39.79 <.0001 Solution for Fixed Effects Standard Effect color Estimate Error DF t Value Pr > |t| Intercept 5.2350 0.2986 19.7 17.53 <.0001 color 1 0.5858 0.3313 20 1.77 0.0923 color 2 0 . . . . cprice 0.1454 0.05081 357 2.86 0.0045 Solution for Random Effects Std Err Effect color rater Estimate Pred DF t Value Pr > |t| Alpha color 1 1 -0.09981 0.4372 19.6 -0.23 0.8218 0.05 color 2 1 0.2895 0.5815 85.3 0.50 0.6199 0.05 color 1 2 -0.5592 0.4372 19.6 -1.28 0.2158 0.05 color 2 2 -0.3984 0.5815 85.3 -0.69 0.4951 0.05 color 1 3 -0.5805 0.4372 19.6 -1.33 0.1995 0.05 color 2 3 -0.7211 0.5815 85.3 -1.24 0.2183 0.05 color 1 4 -0.4539 0.4372 19.6 -1.04 0.3118 0.05 color 2 4 0.4135 0.5815 85.3 0.71 0.4789 0.05 color 1 5 -0.3909 0.4428 21.9 -0.88 0.3869 0.05 color 2 5 -0.2009 1.2048 11.1 -0.17 0.8706 0.05 color 1 6 0.2181 0.4372 19.6 0.50 0.6234 0.05 color 2 6 0.4021 0.5815 85.3 0.69 0.4911 0.05 color 1 7 0.1523 0.4719 15.4 0.32 0.7512 0.05 color 2 7 -1.4964 0.6792 73.3 -2.20 0.0307 0.05 color 1 8 0.2802 0.5176 10.7 0.54 0.5993 0.05 color 2 8 -0.2036 0.6231 83.3 -0.33 0.7446 0.05 color 1 9 -0.4136 0.4372 19.6 -0.95 0.3557 0.05 color 2 9 -0.5438 0.5815 85.3 -0.94 0.3523 0.05 color 1 10 -0.5102 0.4373 19.7 -1.17 0.2573 0.05 color 2 10 1.1292 0.6003 83.9 1.88 0.0634 0.05 color 1 11 -0.07545 0.4372 19.6 -0.17 0.8648 0.05 color 2 11 -0.9098 0.5815 85.3 -1.56 0.1214 0.05 color 1 12 -0.2147 0.4372 19.6 -0.49 0.6289 0.05 color 2 12 0.1175 0.5815 85.3 0.20 0.8403 0.05 color 1 13 -0.4592 0.4372 19.6 -1.05 0.3063 0.05 color 2 13 0.3329 0.5815 85.3 0.57 0.5685 0.05 color 1 14 0.2012 0.4484 18.6 0.45 0.6589 0.05 color 2 14 1.4083 0.7164 65.5 1.97 0.0536 0.05 color 1 15 0.2337 0.5021 12.5 0.47 0.6497 0.05 color 2 15 -0.4324 0.7625 58.3 -0.57 0.5729 0.05 color 1 16 0.3851 0.4372 19.6 0.88 0.3891 0.05 color 2 16 0.5794 0.5815 85.3 1.00 0.3219 0.05 color 1 17 0.8191 0.4372 19.6 1.87 0.0760 0.05 color 2 17 1.6652 0.5815 85.3 2.86 0.0053 0.05 color 1 18 0.4658 0.4847 13.6 0.96 0.3533 0.05 color 2 18 1.7894 0.5819 86.2 3.08 0.0028 0.05 color 1 19 0.4041 0.4372 19.6 0.92 0.3665 0.05 color 2 19 -0.7006 0.5815 85.3 -1.20 0.2316 0.05 color 1 20 0.3905 0.4607 17.4 0.85 0.4082 0.05 color 2 20 -1.8010 0.8209 46.4 -2.19 0.0333 0.05 color 1 21 -0.4052 0.4372 19.6 -0.93 0.3653 0.05 color 2 21 -1.9850 0.5815 85.3 -3.41 0.0010 0.05 color 1 22 -0.3575 0.4712 15.2 -0.76 0.4597 0.05 color 2 22 -0.3345 0.6007 84.6 -0.56 0.5791 0.05 color 1 23 0.9700 0.4372 19.6 2.22 0.0385 0.05 color 2 23 1.6005 0.5815 85.3 2.75 0.0072 0.05 Solution for Random Effects Effect color rater Lower Upper color 1 1 -1.0130 0.8134 color 2 1 -0.8666 1.4455 color 1 2 -1.4724 0.3539 color 2 2 -1.5545 0.7576 color 1 3 -1.4937 0.3326 color 2 3 -1.8771 0.4350 color 1 4 -1.3671 0.4593 color 2 4 -0.7425 1.5696 color 1 5 -1.3094 0.5275 color 2 5 -2.8503 2.4485 color 1 6 -0.6950 1.1313 color 2 6 -0.7540 1.5581 color 1 7 -0.8514 1.1560 color 2 7 -2.8500 -0.1429 color 1 8 -0.8627 1.4231 color 2 8 -1.4428 1.0356 color 1 9 -1.3267 0.4996 color 2 9 -1.6998 0.6123 color 1 10 -1.4234 0.4030 color 2 10 -0.06465 2.3230 color 1 11 -0.9886 0.8377 color 2 11 -2.0659 0.2462 color 1 12 -1.1278 0.6985 color 2 12 -1.0385 1.2735 color 1 13 -1.3724 0.4539 color 2 13 -0.8232 1.4889 color 1 14 -0.7389 1.1413 color 2 14 -0.02226 2.8389 color 1 15 -0.8555 1.3228 color 2 15 -1.9584 1.0937 color 1 16 -0.5280 1.2983 color 2 16 -0.5767 1.7354 color 1 17 -0.09411 1.7322 color 2 17 0.5092 2.8213 color 1 18 -0.5767 1.5083 color 2 18 0.6327 2.9461 color 1 19 -0.5090 1.3173 color 2 19 -1.8566 0.4555 color 1 20 -0.5798 1.3608 color 2 20 -3.4530 -0.1490 color 1 21 -1.3183 0.5080 color 2 21 -3.1411 -0.8290 color 1 22 -1.3610 0.6460 color 2 22 -1.5288 0.8599 color 1 23 0.05689 1.8832 color 2 23 0.4445 2.7566 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F color 1 20 3.13 0.0923 cprice 1 357 8.19 0.0045 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Variance Components Subject Effect rater Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Satterthwaite Class Level Information Class Levels Values color 2 1 2 type 2 1 2 brand 20 Anakena Atlas Peak Barbarana Dragon Barbarana Vina Allarde Bridgman Campo viejo Castillo D Cavino Columbia Crest Dallas Conte Febus Fetzer Flora Springs Maple ridge Montecillo Rabbit Ridge Santa Maria Sobon estates Steel Creek Washington Hills casa lapastolle rater 23 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Dimensions Covariance Parameters 2 Columns in X 8 Columns in Z Per Subject 1 Subjects 23 Max Obs Per Subject 20 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 1723.81167494 1 3 1699.10087504 0.00000452 2 1 1699.09863709 0.00000000 Convergence criteria met. Covariance Parameter Estimates Cov Parm Subject Estimate Alpha Lower Upper Intercept rater 0.5227 0.05 0.2636 1.4895 Residual 3.7927 0.05 3.3029 4.4007 Fit Statistics -2 Res Log Likelihood 1699.1 AIC (smaller is better) 1703.1 AICC (smaller is better) 1703.1 BIC (smaller is better) 1705.4 Solution for Fixed Effects Standard Effect color type Estimate Error DF t Value Pr > |t| Intercept 5.0279 0.2878 126 17.47 <.0001 color 1 1.0287 0.3782 376 2.72 0.0068 color 2 0 . . . . type(color) 1 1 -0.4011 0.3041 377 -1.32 0.1880 type(color) 1 2 0 . . . . type(color) 2 1 0.4616 0.3517 378 1.31 0.1902 type(color) 2 2 0 . . . . cprice 0.2205 0.07089 375 3.11 0.0020 Solution for Random Effects Std Err Effect rater Estimate Pred DF t Value Pr > |t| Alpha Intercept 1 0.03125 0.3959 76.1 0.08 0.9373 0.05 Intercept 2 -0.5558 0.3959 76.1 -1.40 0.1644 0.05 Intercept 3 -0.7025 0.3959 76.1 -1.77 0.0800 0.05 Intercept 4 -0.1522 0.3959 76.1 -0.38 0.7017 0.05 Intercept 5 -0.4161 0.4834 48.3 -0.86 0.3936 0.05 Intercept 6 0.2881 0.3959 76.1 0.73 0.4691 0.05 Intercept 7 -0.4312 0.4491 59 -0.96 0.3408 0.05 Intercept 8 0.05173 0.4585 55.9 0.11 0.9106 0.05 Intercept 9 -0.5191 0.3959 76.1 -1.31 0.1937 0.05 Intercept 10 0.06839 0.4019 74.3 0.17 0.8653 0.05 Intercept 11 -0.4457 0.3959 76.1 -1.13 0.2638 0.05 Intercept 12 -0.1155 0.3959 76.1 -0.29 0.7713 0.05 Intercept 13 -0.1889 0.3959 76.1 -0.48 0.6346 0.05 Intercept 14 0.5903 0.4403 61.9 1.34 0.1849 0.05 Intercept 15 0.01834 0.4937 45.4 0.04 0.9705 0.05 Intercept 16 0.4715 0.3959 76.1 1.19 0.2373 0.05 Intercept 17 1.2053 0.3959 76.1 3.04 0.0032 0.05 Intercept 18 1.0869 0.4237 67.3 2.57 0.0125 0.05 Intercept 19 -0.04213 0.3959 76.1 -0.11 0.9155 0.05 Intercept 20 -0.03233 0.4701 52.3 -0.07 0.9454 0.05 Intercept 21 -1.1061 0.3959 76.1 -2.79 0.0066 0.05 Intercept 22 -0.3828 0.4231 67.5 -0.90 0.3688 0.05 Intercept 23 1.2787 0.3959 76.1 3.23 0.0018 0.05 Solution for Random Effects Effect rater Lower Upper Intercept 1 -0.7572 0.8197 Intercept 2 -1.3442 0.2327 Intercept 3 -1.4910 0.08593 Intercept 4 -0.9407 0.6363 Intercept 5 -1.3880 0.5557 Intercept 6 -0.5004 1.0765 Intercept 7 -1.3298 0.4673 Intercept 8 -0.8667 0.9701 Intercept 9 -1.3075 0.2694 Intercept 10 -0.7324 0.8692 Intercept 11 -1.2342 0.3428 Intercept 12 -0.9040 0.6730 Intercept 13 -0.9773 0.5996 Intercept 14 -0.2898 1.4704 Intercept 15 -0.9759 1.0126 Intercept 16 -0.3169 1.2600 Intercept 17 0.4168 1.9937 Intercept 18 0.2413 1.9324 Intercept 19 -0.8306 0.7463 Intercept 20 -0.9756 0.9109 Intercept 21 -1.8946 -0.3176 Intercept 22 -1.2272 0.4615 Intercept 23 0.4902 2.0671 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F color 1 381 7.55 0.0063 type(color) 2 378 1.37 0.2555 cprice 1 375 9.67 0.0020 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Unstructured Subject Effect rater Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Satterthwaite Class Level Information Class Levels Values color 2 1 2 type 2 1 2 brand 20 Anakena Atlas Peak Barbarana Dragon Barbarana Vina Allarde Bridgman Campo viejo Castillo D Cavino Columbia Crest Dallas Conte Febus Fetzer Flora Springs Maple ridge Montecillo Rabbit Ridge Santa Maria Sobon estates Steel Creek Washington Hills casa lapastolle rater 23 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Dimensions Covariance Parameters 4 Columns in X 8 Columns in Z Per Subject 2 Subjects 23 Max Obs Per Subject 20 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 1723.81167494 1 2 1684.34521605 0.00009444 2 1 1684.29665752 0.00000140 3 1 1684.29597855 0.00000000 Convergence criteria met. Covariance Parameter Estimates Cov Parm Subject Estimate Alpha Lower Upper UN(1,1) rater 0.3949 0.05 0.1606 2.0490 UN(2,1) rater 0.2010 0.05 -0.3306 0.7326 UN(2,2) rater 1.4908 0.05 0.7615 4.1252 Residual 3.4684 0.05 3.0070 4.0454 Fit Statistics -2 Res Log Likelihood 1684.3 AIC (smaller is better) 1692.3 AICC (smaller is better) 1692.4 BIC (smaller is better) 1696.8 Null Model Likelihood Ratio Test DF Chi-Square Pr > ChiSq 3 39.52 <.0001 Solution for Fixed Effects Standard Effect color type Estimate Error DF t Value Pr > |t| Intercept 4.9879 0.3506 38.3 14.22 <.0001 color 1 1.0863 0.4463 64.6 2.43 0.0177 color 2 0 . . . . type(color) 1 1 -0.4187 0.2913 359 -1.44 0.1514 type(color) 1 2 0 . . . . type(color) 2 1 0.4206 0.3393 360 1.24 0.2160 type(color) 2 2 0 . . . . cprice 0.2185 0.06786 352 3.22 0.0014 Solution for Random Effects Std Err Effect color rater Estimate Pred DF t Value Pr > |t| Alpha color 1 1 -0.09892 0.4355 19.3 -0.23 0.8227 0.05 color 2 1 0.2820 0.5803 85.2 0.49 0.6282 0.05 color 1 2 -0.5556 0.4355 19.3 -1.28 0.2172 0.05 color 2 2 -0.4046 0.5803 85.2 -0.70 0.4876 0.05 color 1 3 -0.5767 0.4355 19.3 -1.32 0.2010 0.05 color 2 3 -0.7268 0.5803 85.2 -1.25 0.2138 0.05 color 1 4 -0.4511 0.4355 19.3 -1.04 0.3132 0.05 color 2 4 0.4062 0.5803 85.2 0.70 0.4858 0.05 color 1 5 -0.3876 0.4409 21.5 -0.88 0.3891 0.05 color 2 5 -0.1973 1.1995 11.1 -0.16 0.8723 0.05 color 1 6 0.2172 0.4355 19.3 0.50 0.6236 0.05 color 2 6 0.3942 0.5803 85.2 0.68 0.4988 0.05 color 1 7 0.1325 0.4703 15 0.28 0.7821 0.05 color 2 7 -1.4591 0.6793 72.8 -2.15 0.0350 0.05 color 1 8 0.2751 0.5150 10.5 0.53 0.6044 0.05 color 2 8 -0.2053 0.6217 83.1 -0.33 0.7420 0.05 color 1 9 -0.4107 0.4355 19.3 -0.94 0.3574 0.05 color 2 9 -0.5499 0.5803 85.2 -0.95 0.3460 0.05 color 1 10 -0.5073 0.4356 19.3 -1.16 0.2584 0.05 color 2 10 1.1196 0.5991 83.8 1.87 0.0651 0.05 color 1 11 -0.07434 0.4355 19.3 -0.17 0.8662 0.05 color 2 11 -0.9157 0.5803 85.2 -1.58 0.1183 0.05 color 1 12 -0.2131 0.4355 19.3 -0.49 0.6302 0.05 color 2 12 0.1104 0.5803 85.2 0.19 0.8496 0.05 color 1 13 -0.4563 0.4355 19.3 -1.05 0.3077 0.05 color 2 13 0.3257 0.5803 85.2 0.56 0.5761 0.05 color 1 14 0.2058 0.4467 18.2 0.46 0.6505 0.05 color 2 14 1.4670 0.7182 64.7 2.04 0.0452 0.05 color 1 15 0.2324 0.4997 12.3 0.47 0.6499 0.05 color 2 15 -0.4862 0.7622 57.5 -0.64 0.5261 0.05 color 1 16 0.3832 0.4355 19.3 0.88 0.3898 0.05 color 2 16 0.5711 0.5803 85.2 0.98 0.3278 0.05 color 1 17 0.8144 0.4355 19.3 1.87 0.0768 0.05 color 2 17 1.6551 0.5803 85.2 2.85 0.0054 0.05 color 1 18 0.4149 0.4837 13.3 0.86 0.4063 0.05 color 2 18 1.7745 0.5807 86.1 3.06 0.0030 0.05 color 1 19 0.4025 0.4355 19.3 0.92 0.3668 0.05 color 2 19 -0.7072 0.5803 85.2 -1.22 0.2263 0.05 color 1 20 0.4166 0.4590 17 0.91 0.3768 0.05 color 2 20 -1.7160 0.8217 45.7 -2.09 0.0424 0.05 color 1 21 -0.4019 0.4355 19.3 -0.92 0.3675 0.05 color 2 21 -1.9892 0.5803 85.2 -3.43 0.0009 0.05 color 1 22 -0.3256 0.4698 14.8 -0.69 0.4990 0.05 color 2 22 -0.3388 0.5994 84.5 -0.57 0.5733 0.05 color 1 23 0.9646 0.4355 19.3 2.21 0.0390 0.05 color 2 23 1.5904 0.5803 85.2 2.74 0.0075 0.05 Solution for Random Effects Effect color rater Lower Upper color 1 1 -1.0096 0.8118 color 2 1 -0.8717 1.4357 color 1 2 -1.4663 0.3551 color 2 2 -1.5582 0.7491 color 1 3 -1.4873 0.3340 color 2 3 -1.8804 0.4269 color 1 4 -1.3618 0.4596 color 2 4 -0.7475 1.5599 color 1 5 -1.3034 0.5281 color 2 5 -2.8348 2.4403 color 1 6 -0.6935 1.1279 color 2 6 -0.7595 1.5478 color 1 7 -0.8697 1.1346 color 2 7 -2.8129 -0.1053 color 1 8 -0.8644 1.4146 color 2 8 -1.4419 1.0312 color 1 9 -1.3214 0.5000 color 2 9 -1.7035 0.6038 color 1 10 -1.4181 0.4034 color 2 10 -0.07174 2.3109 color 1 11 -0.9850 0.8363 color 2 11 -2.0694 0.2380 color 1 12 -1.1238 0.6976 color 2 12 -1.0433 1.2640 color 1 13 -1.3670 0.4544 color 2 13 -0.8280 1.4793 color 1 14 -0.7319 1.1434 color 2 14 0.03241 2.9015 color 1 15 -0.8535 1.3184 color 2 15 -2.0121 1.0397 color 1 16 -0.5275 1.2939 color 2 16 -0.5826 1.7248 color 1 17 -0.09628 1.7251 color 2 17 0.5014 2.8088 color 1 18 -0.6282 1.4579 color 2 18 0.6202 2.9288 color 1 19 -0.5082 1.3132 color 2 19 -1.8609 0.4465 color 1 20 -0.5518 1.3850 color 2 20 -3.3704 -0.06172 color 1 21 -1.3126 0.5088 color 2 21 -3.1429 -0.8355 color 1 22 -1.3281 0.6768 color 2 22 -1.5307 0.8530 color 1 23 0.05389 1.8753 color 2 23 0.4367 2.7441 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F color 1 20.9 3.98 0.0592 type(color) 2 360 1.43 0.2401 cprice 1 352 10.37 0.0014 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Variance Components Subject Effect rater Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Satterthwaite Class Level Information Class Levels Values brandnum 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 rater 23 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 color 2 1 2 Dimensions Covariance Parameters 2 Columns in X 23 Columns in Z Per Subject 1 Subjects 23 Max Obs Per Subject 20 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 1667.98186087 1 3 1638.15513840 0.00000386 2 1 1638.15329506 0.00000000 Convergence criteria met. Covariance Parameter Estimates Cov Parm Subject Estimate Alpha Lower Upper Intercept rater 0.5542 0.05 0.2856 1.5024 Residual 3.4541 0.05 2.9997 4.0209 Fit Statistics -2 Res Log Likelihood 1638.2 AIC (smaller is better) 1642.2 AICC (smaller is better) 1642.2 BIC (smaller is better) 1644.4 Solution for Fixed Effects Standard Effect brandnum color Estimate Error DF t Value Intercept 6.0205 0.4558 317 13.21 color 1 -0.2967 0.5967 360 -0.50 color 2 0 . . . brandnum(color) 1 1 0.5630 0.5817 360 0.97 brandnum(color) 2 1 0.7838 0.5756 361 1.36 brandnum(color) 3 1 0.06021 0.5965 360 0.10 brandnum(color) 4 1 -1.5423 0.5965 360 -2.59 brandnum(color) 5 1 -0.09424 0.5893 361 -0.16 brandnum(color) 11 1 0.4962 0.5811 360 0.85 brandnum(color) 12 1 -0.3146 0.5750 360 -0.55 brandnum(color) 13 1 -0.5525 0.5886 360 -0.94 brandnum(color) 14 1 0.2286 0.5757 361 0.40 brandnum(color) 15 1 0 . . . brandnum(color) 6 2 -1.2895 0.6213 360 -2.08 brandnum(color) 7 2 -0.7747 0.6126 360 -1.26 brandnum(color) 8 2 -1.0041 0.6232 362 -1.61 brandnum(color) 9 2 0.3868 0.5967 360 0.65 brandnum(color) 10 2 -1.0959 0.6048 361 -1.81 brandnum(color) 16 2 -2.3808 0.5893 360 -4.04 brandnum(color) 17 2 0.2858 0.5893 360 0.49 brandnum(color) 18 2 -0.6512 0.5958 359 -1.09 brandnum(color) 19 2 0.09662 0.5833 360 0.17 brandnum(color) 20 2 0 . . . Solution for Fixed Effects Effect brandnum color Pr > |t| Intercept <.0001 color 1 0.6193 color 2 . brandnum(color) 1 1 0.3337 brandnum(color) 2 1 0.1742 brandnum(color) 3 1 0.9197 brandnum(color) 4 1 0.0101 brandnum(color) 5 1 0.8730 brandnum(color) 11 1 0.3938 brandnum(color) 12 1 0.5846 brandnum(color) 13 1 0.3485 brandnum(color) 14 1 0.6916 brandnum(color) 15 1 . brandnum(color) 6 2 0.0387 brandnum(color) 7 2 0.2068 brandnum(color) 8 2 0.1080 brandnum(color) 9 2 0.5173 brandnum(color) 10 2 0.0708 brandnum(color) 16 2 <.0001 brandnum(color) 17 2 0.6279 brandnum(color) 18 2 0.2752 brandnum(color) 19 2 0.8685 brandnum(color) 20 2 . Solution for Random Effects Std Err Effect rater Estimate Pred DF t Value Pr > |t| Alpha Intercept 1 0.05167 0.3886 86.8 0.13 0.8945 0.05 Intercept 2 -0.5583 0.3886 86.8 -1.44 0.1544 0.05 Intercept 3 -0.7107 0.3886 86.8 -1.83 0.0708 0.05 Intercept 4 -0.1389 0.3886 86.8 -0.36 0.7215 0.05 Intercept 5 -0.4230 0.4780 58.2 -0.89 0.3798 0.05 Intercept 6 0.3185 0.3886 86.8 0.82 0.4146 0.05 Intercept 7 -0.5788 0.4434 69.8 -1.31 0.1960 0.05 Intercept 8 0.003023 0.4542 66.1 0.01 0.9947 0.05 Intercept 9 -0.5201 0.3886 86.8 -1.34 0.1842 0.05 Intercept 10 0.09400 0.3949 85.2 0.24 0.8124 0.05 Intercept 11 -0.4439 0.3886 86.8 -1.14 0.2564 0.05 Intercept 12 -0.1008 0.3886 86.8 -0.26 0.7959 0.05 Intercept 13 -0.1771 0.3886 86.8 -0.46 0.6498 0.05 Intercept 14 0.6161 0.4337 73.1 1.42 0.1598 0.05 Intercept 15 -0.1434 0.4918 53.9 -0.29 0.7717 0.05 Intercept 16 0.5091 0.3886 86.8 1.31 0.1936 0.05 Intercept 17 1.2715 0.3886 86.8 3.27 0.0015 0.05 Intercept 18 1.1677 0.4169 78.5 2.80 0.0064 0.05 Intercept 19 -0.02457 0.3886 86.8 -0.06 0.9497 0.05 Intercept 20 -0.04677 0.4654 62.3 -0.10 0.9203 0.05 Intercept 21 -1.1301 0.3886 86.8 -2.91 0.0046 0.05 Intercept 22 -0.3829 0.4167 78.6 -0.92 0.3610 0.05 Intercept 23 1.3478 0.3886 86.8 3.47 0.0008 0.05 Solution for Random Effects Effect rater Lower Upper Intercept 1 -0.7206 0.8240 Intercept 2 -1.3306 0.2141 Intercept 3 -1.4831 0.06157 Intercept 4 -0.9112 0.6334 Intercept 5 -1.3797 0.5337 Intercept 6 -0.4538 1.0908 Intercept 7 -1.4631 0.3055 Intercept 8 -0.9038 0.9098 Intercept 9 -1.2925 0.2522 Intercept 10 -0.6911 0.8791 Intercept 11 -1.2162 0.3284 Intercept 12 -0.8731 0.6715 Intercept 13 -0.9494 0.5953 Intercept 14 -0.2483 1.4805 Intercept 15 -1.1294 0.8426 Intercept 16 -0.2632 1.2814 Intercept 17 0.4992 2.0438 Intercept 18 0.3378 1.9976 Intercept 19 -0.7969 0.7477 Intercept 20 -0.9769 0.8834 Intercept 21 -1.9024 -0.3578 Intercept 22 -1.2125 0.4467 Intercept 23 0.5754 2.1201 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F color 1 367 2.67 0.1030 brandnum(color) 18 360 3.46 <.0001 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Unstructured Subject Effect rater Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Satterthwaite Class Level Information Class Levels Values brandnum 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 rater 23 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 color 2 1 2 Dimensions Covariance Parameters 4 Columns in X 21 Columns in Z Per Subject 2 Subjects 23 Max Obs Per Subject 20 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 1667.98186087 1 2 1619.73838298 0.00015043 2 1 1619.66298591 0.00000336 3 1 1619.66141243 0.00000000 Convergence criteria met. Covariance Parameter Estimates Cov Parm Subject Estimate Alpha Lower Upper UN(1,1) rater 0.4043 0.05 0.1726 1.7974 UN(2,1) rater 0.2186 0.05 -0.3150 0.7521 UN(2,2) rater 1.6213 0.05 0.8455 4.2812 Residual 3.0985 0.05 2.6783 3.6265 Fit Statistics -2 Res Log Likelihood 1619.7 AIC (smaller is better) 1627.7 AICC (smaller is better) 1627.8 BIC (smaller is better) 1632.2 Null Model Likelihood Ratio Test DF Chi-Square Pr > ChiSq 3 48.32 <.0001 Solution for Fixed Effects Standard Effect brandnum Estimate Error DF t Value Pr > |t| Intercept 5.8934 0.4899 116 12.03 <.0001 brandnum 1 0.3723 0.6221 182 0.60 0.5503 brandnum 2 0.5824 0.6164 179 0.94 0.3460 brandnum 3 -0.07227 0.6352 190 -0.11 0.9095 brandnum 4 -1.6902 0.6353 190 -2.66 0.0085 brandnum 5 -0.2559 0.6285 187 -0.41 0.6843 brandnum 6 -1.3133 0.5898 337 -2.23 0.0266 brandnum 7 -0.7770 0.5819 338 -1.34 0.1827 brandnum 8 -0.9125 0.5937 340 -1.54 0.1252 brandnum 9 0.4797 0.5670 338 0.85 0.3981 brandnum 10 -1.0626 0.5753 339 -1.85 0.0656 brandnum 11 0.3396 0.6221 182 0.55 0.5858 brandnum 12 -0.4739 0.6163 178 -0.77 0.4430 brandnum 13 -0.6828 0.6282 185 -1.09 0.2784 brandnum 14 0.08097 0.6162 177 0.13 0.8956 brandnum 15 -0.1432 0.6283 185 -0.23 0.8200 brandnum 16 -2.2698 0.5594 338 -4.06 <.0001 brandnum 17 0.3969 0.5594 338 0.71 0.4785 brandnum 18 -0.6330 0.5646 336 -1.12 0.2631 brandnum 19 0.2332 0.5543 339 0.42 0.6742 brandnum 20 0 . . . . Solution for Random Effects Std Err Effect rater color Estimate Pred DF t Value Pr > |t| Alpha color 1 1 -0.08964 0.4259 24.6 -0.21 0.8350 0.05 color 1 2 0.3171 0.5680 91.2 0.56 0.5780 0.05 color 2 1 -0.5708 0.4259 24.6 -1.34 0.1924 0.05 color 2 2 -0.3906 0.5680 91.2 -0.69 0.4933 0.05 color 3 1 -0.5911 0.4259 24.6 -1.39 0.1776 0.05 color 3 2 -0.7242 0.5680 91.2 -1.28 0.2055 0.05 color 4 1 -0.4648 0.4259 24.6 -1.09 0.2856 0.05 color 4 2 0.4482 0.5680 91.2 0.79 0.4320 0.05 color 5 1 -0.3958 0.4313 27.5 -0.92 0.3668 0.05 color 5 2 -0.2140 1.2480 12 -0.17 0.8667 0.05 color 6 1 0.2458 0.4259 24.6 0.58 0.5691 0.05 color 6 2 0.4310 0.5680 91.2 0.76 0.4499 0.05 color 7 1 0.05261 0.4627 19 0.11 0.9107 0.05 color 7 2 -1.6757 0.6676 84.6 -2.51 0.0140 0.05 color 8 1 0.2294 0.5119 12.9 0.45 0.6615 0.05 color 8 2 -0.2332 0.6105 92.1 -0.38 0.7033 0.05 color 9 1 -0.4158 0.4259 24.6 -0.98 0.3384 0.05 color 9 2 -0.5421 0.5680 91.2 -0.95 0.3423 0.05 color 10 1 -0.5282 0.4260 24.7 -1.24 0.2266 0.05 color 10 2 1.2039 0.5873 91.3 2.05 0.0432 0.05 color 11 1 -0.05584 0.4259 24.6 -0.13 0.8967 0.05 color 11 2 -0.9234 0.5680 91.2 -1.63 0.1074 0.05 color 12 1 -0.2099 0.4259 24.6 -0.49 0.6264 0.05 color 12 2 0.1402 0.5680 91.2 0.25 0.8056 0.05 color 13 1 -0.4699 0.4259 24.6 -1.10 0.2805 0.05 color 13 2 0.3649 0.5680 91.2 0.64 0.5222 0.05 color 14 1 0.2069 0.4377 23.2 0.47 0.6409 0.05 color 14 2 1.5629 0.7059 77.3 2.21 0.0298 0.05 color 15 1 0.1123 0.4948 15.2 0.23 0.8235 0.05 color 15 2 -0.6906 0.7564 69.1 -0.91 0.3644 0.05 color 16 1 0.4211 0.4259 24.6 0.99 0.3324 0.05 color 16 2 0.6130 0.5680 91.2 1.08 0.2833 0.05 color 17 1 0.8726 0.4259 24.6 2.05 0.0513 0.05 color 17 2 1.7326 0.5680 91.2 3.05 0.0030 0.05 color 18 1 0.4672 0.4769 16.7 0.98 0.3413 0.05 color 18 2 1.8609 0.5683 92 3.27 0.0015 0.05 color 19 1 0.4498 0.4259 24.6 1.06 0.3011 0.05 color 19 2 -0.7109 0.5680 91.2 -1.25 0.2139 0.05 color 20 1 0.4358 0.4508 21.5 0.97 0.3444 0.05 color 20 2 -1.8878 0.8171 55.9 -2.31 0.0246 0.05 color 21 1 -0.3972 0.4259 24.6 -0.93 0.3600 0.05 color 21 2 -2.0328 0.5680 91.2 -3.58 0.0006 0.05 color 22 1 -0.3371 0.4623 18.7 -0.73 0.4749 0.05 color 22 2 -0.3137 0.5875 91.9 -0.53 0.5947 0.05 color 23 1 1.0327 0.4259 24.6 2.42 0.0230 0.05 color 23 2 1.6644 0.5680 91.2 2.93 0.0043 0.05 Solution for Random Effects Effect rater color Lower Upper color 1 1 -0.9674 0.7882 color 1 2 -0.8111 1.4453 color 2 1 -1.4486 0.3070 color 2 2 -1.5188 0.7375 color 3 1 -1.4689 0.2867 color 3 2 -1.8523 0.4040 color 4 1 -1.3426 0.4130 color 4 2 -0.6799 1.5764 color 5 1 -1.2799 0.4884 color 5 2 -2.9341 2.5062 color 6 1 -0.6320 1.1236 color 6 2 -0.6972 1.5592 color 7 1 -0.9160 1.0212 color 7 2 -3.0032 -0.3483 color 8 1 -0.8773 1.3360 color 8 2 -1.4456 0.9792 color 9 1 -1.2936 0.4620 color 9 2 -1.6703 0.5860 color 10 1 -1.4061 0.3496 color 10 2 0.03743 2.3704 color 11 1 -0.9336 0.8220 color 11 2 -2.0516 0.2047 color 12 1 -1.0877 0.6679 color 12 2 -0.9880 1.2683 color 13 1 -1.3477 0.4079 color 13 2 -0.7633 1.4930 color 14 1 -0.6981 1.1119 color 14 2 0.1574 2.9684 color 15 1 -0.9411 1.1658 color 15 2 -2.1996 0.8183 color 16 1 -0.4567 1.2989 color 16 2 -0.5151 1.7412 color 17 1 -0.00520 1.7504 color 17 2 0.6044 2.8607 color 18 1 -0.5405 1.4748 color 18 2 0.7322 2.9897 color 19 1 -0.4280 1.3276 color 19 2 -1.8390 0.4173 color 20 1 -0.5003 1.3720 color 20 2 -3.5246 -0.2509 color 21 1 -1.2750 0.4806 color 21 2 -3.1609 -0.9046 color 22 1 -1.3058 0.6315 color 22 2 -1.4807 0.8532 color 23 1 0.1549 1.9105 color 23 2 0.5363 2.7926 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F brandnum 19 206 3.74 <.0001 The SAS System The Mixed Procedure Model Information Data Set WORK.TWO Dependent Variable score Covariance Structure Variance Components Subject Effect rater Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Satterthwaite Class Level Information Class Levels Values brandnum 20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 rater 23 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Dimensions Covariance Parameters 2 Columns in X 20 Columns in Z Per Subject 1 Subjects 23 Max Obs Per Subject 20 Number of Observations Number of Observations Read 460 Number of Observations Used 400 Number of Observations Not Used 60 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 1667.98186087 1 3 1638.15513840 0.00000386 2 1 1638.15329506 0.00000000 Convergence criteria met. Covariance Parameter Estimates Cov Parm Subject Estimate Alpha Lower Upper Intercept rater 0.5542 0.05 0.2856 1.5024 Residual 3.4541 0.05 2.9997 4.0209 Fit Statistics -2 Res Log Likelihood 1638.2 AIC (smaller is better) 1642.2 AICC (smaller is better) 1642.2 BIC (smaller is better) 1644.4 Solution for Fixed Effects Standard Effect brandnum Estimate Error DF t Value Pr > |t| brandnum 1 6.2869 0.4352 304 14.45 <.0001 brandnum 2 6.5076 0.4259 298 15.28 <.0001 brandnum 3 5.7840 0.4556 318 12.69 <.0001 brandnum 4 4.1815 0.4556 318 9.18 <.0001 brandnum 5 5.6296 0.4449 311 12.65 <.0001 brandnum 6 4.7310 0.4797 331 9.86 <.0001 brandnum 7 5.2458 0.4672 324 11.23 <.0001 brandnum 8 5.0164 0.4795 332 10.46 <.0001 brandnum 9 6.4073 0.4450 311 14.40 <.0001 brandnum 10 4.9246 0.4557 318 10.81 <.0001 brandnum 11 6.2200 0.4351 305 14.30 <.0001 brandnum 12 5.4092 0.4260 298 12.70 <.0001 brandnum 13 5.1713 0.4450 311 11.62 <.0001 brandnum 14 5.9524 0.4260 297 13.97 <.0001 brandnum 15 5.7238 0.4450 311 12.86 <.0001 brandnum 16 3.6397 0.4353 304 8.36 <.0001 brandnum 17 6.3064 0.4353 304 14.49 <.0001 brandnum 18 5.3693 0.4452 311 12.06 <.0001 brandnum 19 6.1171 0.4261 297 14.36 <.0001 brandnum 20 6.0205 0.4558 317 13.21 <.0001 Solution for Random Effects Std Err Effect rater Estimate Pred DF t Value Pr > |t| Alpha Intercept 1 0.05167 0.3886 86.8 0.13 0.8945 0.05 Intercept 2 -0.5583 0.3886 86.8 -1.44 0.1544 0.05 Intercept 3 -0.7107 0.3886 86.8 -1.83 0.0708 0.05 Intercept 4 -0.1389 0.3886 86.8 -0.36 0.7215 0.05 Intercept 5 -0.4230 0.4780 58.2 -0.89 0.3798 0.05 Intercept 6 0.3185 0.3886 86.8 0.82 0.4146 0.05 Intercept 7 -0.5788 0.4434 69.8 -1.31 0.1960 0.05 Intercept 8 0.003023 0.4542 66.1 0.01 0.9947 0.05 Intercept 9 -0.5201 0.3886 86.8 -1.34 0.1842 0.05 Intercept 10 0.09400 0.3949 85.2 0.24 0.8124 0.05 Intercept 11 -0.4439 0.3886 86.8 -1.14 0.2564 0.05 Intercept 12 -0.1008 0.3886 86.8 -0.26 0.7959 0.05 Intercept 13 -0.1771 0.3886 86.8 -0.46 0.6498 0.05 Intercept 14 0.6161 0.4337 73.1 1.42 0.1598 0.05 Intercept 15 -0.1434 0.4918 53.9 -0.29 0.7717 0.05 Intercept 16 0.5091 0.3886 86.8 1.31 0.1936 0.05 Intercept 17 1.2715 0.3886 86.8 3.27 0.0015 0.05 Intercept 18 1.1677 0.4169 78.5 2.80 0.0064 0.05 Intercept 19 -0.02457 0.3886 86.8 -0.06 0.9497 0.05 Intercept 20 -0.04677 0.4654 62.3 -0.10 0.9203 0.05 Intercept 21 -1.1301 0.3886 86.8 -2.91 0.0046 0.05 Intercept 22 -0.3829 0.4167 78.6 -0.92 0.3610 0.05 Intercept 23 1.3478 0.3886 86.8 3.47 0.0008 0.05 Solution for Random Effects Effect rater Lower Upper Intercept 1 -0.7206 0.8240 Intercept 2 -1.3306 0.2141 Intercept 3 -1.4831 0.06157 Intercept 4 -0.9112 0.6334 Intercept 5 -1.3797 0.5337 Intercept 6 -0.4538 1.0908 Intercept 7 -1.4631 0.3055 Intercept 8 -0.9038 0.9098 Intercept 9 -1.2925 0.2522 Intercept 10 -0.6911 0.8791 Intercept 11 -1.2162 0.3284 Intercept 12 -0.8731 0.6715 Intercept 13 -0.9494 0.5953 Intercept 14 -0.2483 1.4805 Intercept 15 -1.1294 0.8426 Intercept 16 -0.2632 1.2814 Intercept 17 0.4992 2.0438 Intercept 18 0.3378 1.9976 Intercept 19 -0.7969 0.7477 Intercept 20 -0.9769 0.8834 Intercept 21 -1.9024 -0.3578 Intercept 22 -1.2125 0.4467 Intercept 23 0.5754 2.1201 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F brandnum 20 200 50.03 <.0001 Least Squares Means Standard Effect brandnum Estimate Error DF t Value Pr > |t| brandnum 1 6.2869 0.4352 304 14.45 <.0001 brandnum 2 6.5076 0.4259 298 15.28 <.0001 brandnum 3 5.7840 0.4556 318 12.69 <.0001 brandnum 4 4.1815 0.4556 318 9.18 <.0001 brandnum 5 5.6296 0.4449 311 12.65 <.0001 brandnum 6 4.7310 0.4797 331 9.86 <.0001 brandnum 7 5.2458 0.4672 324 11.23 <.0001 brandnum 8 5.0164 0.4795 332 10.46 <.0001 brandnum 9 6.4073 0.4450 311 14.40 <.0001 brandnum 10 4.9246 0.4557 318 10.81 <.0001 brandnum 11 6.2200 0.4351 305 14.30 <.0001 brandnum 12 5.4092 0.4260 298 12.70 <.0001 brandnum 13 5.1713 0.4450 311 11.62 <.0001 brandnum 14 5.9524 0.4260 297 13.97 <.0001 brandnum 15 5.7238 0.4450 311 12.86 <.0001 brandnum 16 3.6397 0.4353 304 8.36 <.0001 brandnum 17 6.3064 0.4353 304 14.49 <.0001 brandnum 18 5.3693 0.4452 311 12.06 <.0001 brandnum 19 6.1171 0.4261 297 14.36 <.0001 brandnum 20 6.0205 0.4558 317 13.21 <.0001 Differences of Least Squares Means Standard Effect brandnum _brandnum Estimate Error DF t Value Pr > |t| brandnum 1 2 -0.2208 0.5674 360 -0.39 0.6975 brandnum 1 3 0.5028 0.5899 360 0.85 0.3946 brandnum 1 4 2.1054 0.5892 360 3.57 0.0004 brandnum 1 5 0.6573 0.5819 360 1.13 0.2594 brandnum 1 6 1.5559 0.6089 361 2.56 0.0110 brandnum 1 7 1.0411 0.5990 361 1.74 0.0831 brandnum 1 8 1.2705 0.6097 362 2.08 0.0379 brandnum 1 9 -0.1204 0.5827 361 -0.21 0.8364 brandnum 1 10 1.3623 0.5909 362 2.31 0.0217 brandnum 1 11 0.06687 0.5750 361 0.12 0.9075 brandnum 1 12 0.8776 0.5681 360 1.54 0.1233 brandnum 1 13 1.1155 0.5817 360 1.92 0.0560 brandnum 1 14 0.3345 0.5681 360 0.59 0.5564 brandnum 1 15 0.5630 0.5817 360 0.97 0.3337 brandnum 1 16 2.6472 0.5743 360 4.61 <.0001 brandnum 1 17 -0.01949 0.5743 360 -0.03 0.9729 brandnum 1 18 0.9175 0.5819 360 1.58 0.1157 brandnum 1 19 0.1697 0.5682 360 0.30 0.7653 brandnum 1 20 0.2664 0.5901 361 0.45 0.6520 brandnum 2 3 0.7236 0.5839 361 1.24 0.2161 brandnum 2 4 2.3261 0.5833 360 3.99 <.0001 brandnum 2 5 0.8780 0.5749 360 1.53 0.1276 brandnum 2 6 1.7766 0.6030 362 2.95 0.0034 brandnum 2 7 1.2618 0.5931 362 2.13 0.0341 brandnum 2 8 1.4912 0.6028 362 2.47 0.0138 brandnum 2 9 0.1003 0.5757 361 0.17 0.8618 brandnum 2 10 1.5830 0.5840 361 2.71 0.0070 brandnum 2 11 0.2876 0.5680 360 0.51 0.6129 brandnum 2 12 1.0984 0.5610 360 1.96 0.0510 brandnum 2 13 1.3363 0.5757 361 2.32 0.0208 brandnum 2 14 0.5552 0.5610 360 0.99 0.3230 brandnum 2 15 0.7838 0.5756 361 1.36 0.1742 brandnum 2 16 2.8679 0.5681 360 5.05 <.0001 brandnum 2 17 0.2013 0.5681 360 0.35 0.7234 brandnum 2 18 1.1383 0.5758 361 1.98 0.0488 brandnum 2 19 0.3905 0.5611 360 0.70 0.4869 brandnum 2 20 0.4871 0.5841 361 0.83 0.4048 brandnum 3 4 1.6025 0.6037 360 2.65 0.0083 brandnum 3 5 0.1545 0.5966 360 0.26 0.7959 brandnum 3 6 1.0530 0.6215 360 1.69 0.0911 brandnum 3 7 0.5383 0.6128 361 0.88 0.3803 brandnum 3 8 0.7677 0.6233 362 1.23 0.2189 brandnum 3 9 -0.6233 0.5977 362 -1.04 0.2977 brandnum 3 10 0.8594 0.6049 361 1.42 0.1563 brandnum 3 11 -0.4360 0.5900 361 -0.74 0.4605 brandnum 3 12 0.3748 0.5832 360 0.64 0.5209 brandnum 3 13 0.6127 0.5974 361 1.03 0.3058 brandnum 3 14 -0.1684 0.5840 361 -0.29 0.7733 brandnum 3 15 0.06021 0.5965 360 0.10 0.9197 brandnum 3 16 2.1444 0.5901 361 3.63 0.0003 brandnum 3 17 -0.5223 0.5901 361 -0.89 0.3767 brandnum 3 18 0.4147 0.5975 361 0.69 0.4881 brandnum 3 19 -0.3331 0.5841 361 -0.57 0.5688 brandnum 3 20 -0.2365 0.6048 361 -0.39 0.6960 brandnum 4 5 -1.4481 0.5959 360 -2.43 0.0156 brandnum 4 6 -0.5495 0.6223 361 -0.88 0.3778 brandnum 4 7 -1.0643 0.6136 361 -1.73 0.0837 brandnum 4 8 -0.8349 0.6242 363 -1.34 0.1819 brandnum 4 9 -2.2258 0.5984 362 -3.72 0.0002 brandnum 4 10 -0.7431 0.6057 362 -1.23 0.2207 brandnum 4 11 -2.0385 0.5900 361 -3.46 0.0006 brandnum 4 12 -1.2277 0.5832 360 -2.11 0.0360 brandnum 4 13 -0.9898 0.5974 361 -1.66 0.0984 brandnum 4 14 -1.7709 0.5840 361 -3.03 0.0026 brandnum 4 15 -1.5423 0.5965 360 -2.59 0.0101 brandnum 4 16 0.5418 0.5901 361 0.92 0.3591 brandnum 4 17 -2.1249 0.5901 361 -3.60 0.0004 brandnum 4 18 -1.1878 0.5975 361 -1.99 0.0476 brandnum 4 19 -1.9356 0.5841 361 -3.31 0.0010 brandnum 4 20 -1.8390 0.6047 361 -3.04 0.0025 brandnum 5 6 0.8986 0.6154 361 1.46 0.1451 brandnum 5 7 0.3838 0.6065 362 0.63 0.5273 brandnum 5 8 0.6132 0.6161 362 1.00 0.3202 brandnum 5 9 -0.7777 0.5901 362 -1.32 0.1884 brandnum 5 10 0.7050 0.5975 361 1.18 0.2388 brandnum 5 11 -0.5904 0.5817 360 -1.01 0.3108 brandnum 5 12 0.2204 0.5749 360 0.38 0.7017 brandnum 5 13 0.4582 0.5901 362 0.78 0.4379 brandnum 5 14 -0.3228 0.5757 361 -0.56 0.5753 brandnum 5 15 -0.09424 0.5893 361 -0.16 0.8730 brandnum 5 16 1.9899 0.5827 361 3.41 0.0007 brandnum 5 17 -0.6768 0.5827 361 -1.16 0.2462 brandnum 5 18 0.2603 0.5903 362 0.44 0.6595 brandnum 5 19 -0.4875 0.5757 361 -0.85 0.3976 brandnum 5 20 -0.3909 0.5976 361 -0.65 0.5134 brandnum 6 7 -0.5148 0.6290 359 -0.82 0.4137 brandnum 6 8 -0.2854 0.6394 361 -0.45 0.6556 brandnum 6 9 -1.6763 0.6145 360 -2.73 0.0067 brandnum 6 10 -0.1936 0.6215 360 -0.31 0.7556 brandnum 6 11 -1.4890 0.6089 362 -2.45 0.0150 brandnum 6 12 -0.6782 0.6023 361 -1.13 0.2609 brandnum 6 13 -0.4403 0.6152 361 -0.72 0.4746 brandnum 6 14 -1.2214 0.6022 361 -2.03 0.0433 brandnum 6 15 -0.9928 0.6153 361 -1.61 0.1075 brandnum 6 16 1.0913 0.6080 361 1.79 0.0735 brandnum 6 17 -1.5754 0.6080 361 -2.59 0.0100 brandnum 6 18 -0.6383 0.6144 360 -1.04 0.2995 brandnum 6 19 -1.3861 0.6022 361 -2.30 0.0219 brandnum 6 20 -1.2895 0.6213 360 -2.08 0.0387 brandnum 7 8 0.2294 0.6299 360 0.36 0.7160 brandnum 7 9 -1.1615 0.6047 360 -1.92 0.0556 brandnum 7 10 0.3212 0.6118 360 0.52 0.6000 brandnum 7 11 -0.9742 0.5999 362 -1.62 0.1053 brandnum 7 12 -0.1634 0.5932 362 -0.28 0.7831 brandnum 7 13 0.07444 0.6055 361 0.12 0.9022 brandnum 7 14 -0.7066 0.5923 361 -1.19 0.2337 brandnum 7 15 -0.4781 0.6064 362 -0.79 0.4310 brandnum 7 16 1.6061 0.5982 360 2.68 0.0076 brandnum 7 17 -1.0606 0.5982 360 -1.77 0.0771 brandnum 7 18 -0.1236 0.6046 360 -0.20 0.8382 brandnum 7 19 -0.8714 0.5923 361 -1.47 0.1421 brandnum 7 20 -0.7747 0.6126 360 -1.26 0.2068 brandnum 8 9 -1.3909 0.6142 360 -2.26 0.0241 brandnum 8 10 0.09178 0.6212 360 0.15 0.8826 brandnum 8 11 -1.2036 0.6089 362 -1.98 0.0488 brandnum 8 12 -0.3928 0.6029 362 -0.65 0.5151 brandnum 8 13 -0.1550 0.6153 361 -0.25 0.8013 brandnum 8 14 -0.9360 0.6020 361 -1.55 0.1209 brandnum 8 15 -0.7074 0.6163 362 -1.15 0.2518 brandnum 8 16 1.3767 0.6088 362 2.26 0.0243 brandnum 8 17 -1.2900 0.6088 362 -2.12 0.0348 brandnum 8 18 -0.3530 0.6152 361 -0.57 0.5665 brandnum 8 19 -1.1007 0.6020 361 -1.83 0.0683 brandnum 8 20 -1.0041 0.6232 362 -1.61 0.1080 brandnum 9 10 1.4827 0.5958 359 2.49 0.0133 brandnum 9 11 0.1873 0.5826 361 0.32 0.7480 brandnum 9 12 0.9981 0.5758 361 1.73 0.0839 brandnum 9 13 1.2360 0.5894 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