The SAS System 1 13:31 Thursday, January 12, 2012 The Mixed Procedure Model Information Data Set WORK.DYAD Dependent Variable i_perform Covariance Structure Variance Components Subject Effect dyad Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Containment Class Level Information Class Levels Values dyad 33 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 Dimensions Covariance Parameters 2 Columns in X 1 Columns in Z Per Subject 1 Subjects 33 Max Obs Per Subject 2 Number of Observations Number of Observations Read 66 Number of Observations Used 66 Number of Observations Not Used 0 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 172.31867747 1 1 150.27716773 0.00000000 Convergence criteria met. The SAS System 2 13:31 Thursday, January 12, 2012 The Mixed Procedure Covariance Parameter Estimates Cov Parm Subject Estimate Intercept dyad 0.5503 Residual 0.2359 Fit Statistics -2 Res Log Likelihood 150.3 AIC (smaller is better) 154.3 AICC (smaller is better) 154.5 BIC (smaller is better) 157.3 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 3.8892 0.1423 32 27.33 <.0001 The SAS System 3 13:31 Thursday, January 12, 2012 The Mixed Procedure Model Information Data Set WORK.DYAD Dependent Variable i_perform Covariance Structure Variance Components Subject Effect dyad Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Containment Class Level Information Class Levels Values dyad 33 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 Dimensions Covariance Parameters 2 Columns in X 4 Columns in Z Per Subject 1 Subjects 33 Max Obs Per Subject 2 Number of Observations Number of Observations Read 66 Number of Observations Used 66 Number of Observations Not Used 0 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 157.86674887 1 1 144.86238524 0.00000000 Convergence criteria met. The SAS System 4 13:31 Thursday, January 12, 2012 The Mixed Procedure Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr > Z Intercept dyad 0.3216 0.1164 2.76 0.0029 Residual 0.2305 0.05763 4.00 <.0001 Fit Statistics -2 Res Log Likelihood 144.9 AIC (smaller is better) 148.9 AICC (smaller is better) 149.1 BIC (smaller is better) 151.9 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept -0.4811 1.0211 30 -0.47 0.6410 i_motivate 0.02430 0.01824 32 1.33 0.1921 d_motivate 0.01074 0.04040 32 0.27 0.7921 d_cohesion 0.9179 0.2741 32 3.35 0.0021 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F i_motivate 1 32 1.78 0.1921 d_motivate 1 32 0.07 0.7921 d_cohesion 1 32 11.21 0.0021 The SAS System 5 13:31 Thursday, January 12, 2012 The Mixed Procedure Model Information Data Set WORK.DYAD Dependent Variable i_perform Covariance Structure Unstructured Subject Effect dyad Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Containment Class Level Information Class Levels Values dyad 33 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 Dimensions Covariance Parameters 4 Columns in X 4 Columns in Z Per Subject 2 Subjects 33 Max Obs Per Subject 2 Number of Observations Number of Observations Read 66 Number of Observations Used 66 Number of Observations Not Used 0 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 157.86674887 1 3 138.59025257 0.05684851 2 1 137.70099966 0.02095272 3 1 137.39899067 0.00404011 4 1 137.34546856 0.00022216 5 1 137.34276576 0.00000090 6 1 137.34275521 0.00000000 The SAS System 6 13:31 Thursday, January 12, 2012 The Mixed Procedure Convergence criteria met. Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr Z UN(1,1) dyad 1.9087 1.1265 1.69 0.0451 UN(2,1) dyad -0.08694 0.06433 -1.35 0.1765 UN(2,2) dyad 0.004614 0.003822 1.21 0.1136 Residual 0.1456 0.05354 2.72 0.0033 Fit Statistics -2 Res Log Likelihood 137.3 AIC (smaller is better) 145.3 AICC (smaller is better) 146.0 BIC (smaller is better) 151.3 Null Model Likelihood Ratio Test DF Chi-Square Pr > ChiSq 3 20.52 0.0001 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept -0.5216 1.0029 30 -0.52 0.6068 i_motivate 0.01582 0.02421 30 0.65 0.5185 d_motivate 0.02633 0.03919 2 0.67 0.5709 d_cohesion 0.9010 0.2583 2 3.49 0.0732 Solution for Random Effects Std Err Effect dyad Estimate Pred DF t Value Pr > |t| Intercept 1 -1.2616 0.8623 2 -1.46 0.2810 i_motivate 1 0.03520 0.05583 2 0.63 0.5928 Intercept 2 -0.6969 1.0335 2 -0.67 0.5696 i_motivate 2 0.04542 0.06022 2 0.75 0.5294 The SAS System 7 13:31 Thursday, January 12, 2012 The Mixed Procedure Solution for Random Effects Std Err Effect dyad Estimate Pred DF t Value Pr > |t| Intercept 3 0.1868 0.8530 2 0.22 0.8470 i_motivate 3 -0.00752 0.05206 2 -0.14 0.8984 Intercept 4 0.3904 1.3265 2 0.29 0.7962 i_motivate 4 0.000043 0.06773 2 0.00 0.9995 Intercept 5 0.02413 1.3113 2 0.02 0.9870 i_motivate 5 -0.00103 0.05738 2 -0.02 0.9873 Intercept 6 -0.3643 1.1983 2 -0.30 0.7898 i_motivate 6 0.01291 0.06229 2 0.21 0.8549 Intercept 7 0.09586 1.2871 2 0.07 0.9474 i_motivate 7 -0.03297 0.06453 2 -0.51 0.6602 Intercept 8 1.1118 0.6985 2 1.59 0.2525 i_motivate 8 -0.05286 0.04688 2 -1.13 0.3766 Intercept 9 -0.6988 0.8275 2 -0.84 0.4873 i_motivate 9 0.02656 0.05126 2 0.52 0.6560 Intercept 10 0.3014 1.2952 2 0.23 0.8377 i_motivate 10 -0.00159 0.06788 2 -0.02 0.9835 Intercept 11 1.5304 0.5329 2 2.87 0.1029 i_motivate 11 -0.04067 0.03083 2 -1.32 0.3179 Intercept 12 -1.4500 0.7016 2 -2.07 0.1747 i_motivate 12 0.05874 0.04854 2 1.21 0.3498 Intercept 13 -0.9585 0.7628 2 -1.26 0.3358 i_motivate 13 0.06423 0.04084 2 1.57 0.2564 Intercept 14 0.6172 1.2511 2 0.49 0.6706 i_motivate 14 -0.00393 0.06584 2 -0.06 0.9579 Intercept 15 -0.1989 1.3656 2 -0.15 0.8976 i_motivate 15 -0.02350 0.06560 2 -0.36 0.7545 Intercept 16 0.4511 1.0639 2 0.42 0.7128 i_motivate 16 -0.01855 0.06168 2 -0.30 0.7920 Intercept 17 -0.1120 0.8695 2 -0.13 0.9093 i_motivate 17 0.001013 0.05295 2 0.02 0.9865 Intercept 18 0.5675 1.3435 2 0.42 0.7138 i_motivate 18 -0.03329 0.06346 2 -0.52 0.6522 Intercept 19 0.8193 0.6996 2 1.17 0.3622 i_motivate 19 -0.03484 0.04035 2 -0.86 0.4789 Intercept 20 1.0078 1.0698 2 0.94 0.4456 i_motivate 20 -0.02770 0.06353 2 -0.44 0.7054 Intercept 21 0.7928 0.8733 2 0.91 0.4598 i_motivate 21 -0.03261 0.05463 2 -0.60 0.6111 Intercept 22 -0.3963 1.1836 2 -0.33 0.7696 i_motivate 22 0.03606 0.06337 2 0.57 0.6267 Intercept 23 0.3048 0.9255 2 0.33 0.7732 i_motivate 23 -0.00941 0.04915 2 -0.19 0.8658 Intercept 24 -0.2240 0.6001 2 -0.37 0.7448 i_motivate 24 -0.02475 0.03871 2 -0.64 0.5881 The SAS System 8 13:31 Thursday, January 12, 2012 The Mixed Procedure Solution for Random Effects Std Err Effect dyad Estimate Pred DF t Value Pr > |t| Intercept 25 -0.1554 1.2525 2 -0.12 0.9126 i_motivate 25 0.007217 0.06661 2 0.11 0.9236 Intercept 26 -0.07723 1.3658 2 -0.06 0.9601 i_motivate 26 0.006625 0.06567 2 0.10 0.9288 Intercept 27 0.001963 1.3138 2 0.00 0.9989 i_motivate 27 -0.00309 0.06356 2 -0.05 0.9656 Intercept 28 -2.5071 0.7303 2 -3.43 0.0754 i_motivate 28 0.08223 0.04258 2 1.93 0.1932 Intercept 29 -0.1769 1.2876 2 -0.14 0.9033 i_motivate 29 -0.00293 0.06766 2 -0.04 0.9694 Intercept 30 -1.4032 0.6599 2 -2.13 0.1673 i_motivate 30 0.08847 0.03642 2 2.43 0.1358 Intercept 31 1.9734 0.9999 2 1.97 0.1872 i_motivate 31 -0.06124 0.05820 2 -1.05 0.4031 Intercept 32 -0.1210 1.2761 2 -0.09 0.9331 i_motivate 32 -0.03260 0.06588 2 -0.49 0.6697 Intercept 33 0.6256 1.1568 2 0.54 0.6428 i_motivate 33 -0.01964 0.06390 2 -0.31 0.7877 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F i_motivate 1 30 0.43 0.5185 d_motivate 1 2 0.45 0.5709 d_cohesion 1 2 12.17 0.0732 The SAS System 9 13:31 Thursday, January 12, 2012 The Mixed Procedure Model Information Data Set WORK.DYAD Dependent Variable i_perform Covariance Structure Unstructured Subject Effect dyad Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Containment Class Level Information Class Levels Values dyad 33 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 Dimensions Covariance Parameters 4 Columns in X 4 Columns in Z Per Subject 2 Subjects 33 Max Obs Per Subject 2 Number of Observations Number of Observations Read 66 Number of Observations Used 66 Number of Observations Not Used 0 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 157.86674887 1 3 138.59025257 0.05684851 2 1 137.70099966 0.02095272 3 1 137.39899067 0.00404011 4 1 137.34546856 0.00022216 5 1 137.34276576 0.00000090 6 1 137.34275521 0.00000000 The SAS System 10 13:31 Thursday, January 12, 2012 The Mixed Procedure Convergence criteria met. Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr Z UN(1,1) dyad 1.9087 1.1265 1.69 0.0451 UN(2,1) dyad -0.08694 0.06433 -1.35 0.1765 UN(2,2) dyad 0.004614 0.003822 1.21 0.1136 Residual 0.1456 0.05354 2.72 0.0033 Fit Statistics -2 Res Log Likelihood 137.3 AIC (smaller is better) 145.3 AICC (smaller is better) 146.0 BIC (smaller is better) 151.3 Null Model Likelihood Ratio Test DF Chi-Square Pr > ChiSq 3 20.52 0.0001 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 0.005347 1.2181 30 0.00 0.9965 i_motivate 0.01582 0.02421 30 0.65 0.5185 d_motivate_lo 0.02633 0.03919 2 0.67 0.5709 d_cohesion 0.9010 0.2583 2 3.49 0.0732 Solution for Random Effects Std Err Effect dyad Estimate Pred DF t Value Pr > |t| Intercept 1 -1.2616 0.8623 2 -1.46 0.2810 i_motivate 1 0.03520 0.05583 2 0.63 0.5928 Intercept 2 -0.6969 1.0335 2 -0.67 0.5696 i_motivate 2 0.04542 0.06022 2 0.75 0.5294 The SAS System 11 13:31 Thursday, January 12, 2012 The Mixed Procedure Solution for Random Effects Std Err Effect dyad Estimate Pred DF t Value Pr > |t| Intercept 3 0.1868 0.8530 2 0.22 0.8470 i_motivate 3 -0.00752 0.05206 2 -0.14 0.8984 Intercept 4 0.3904 1.3265 2 0.29 0.7962 i_motivate 4 0.000043 0.06773 2 0.00 0.9995 Intercept 5 0.02413 1.3113 2 0.02 0.9870 i_motivate 5 -0.00103 0.05738 2 -0.02 0.9873 Intercept 6 -0.3643 1.1983 2 -0.30 0.7898 i_motivate 6 0.01291 0.06229 2 0.21 0.8549 Intercept 7 0.09586 1.2871 2 0.07 0.9474 i_motivate 7 -0.03297 0.06453 2 -0.51 0.6602 Intercept 8 1.1118 0.6985 2 1.59 0.2525 i_motivate 8 -0.05286 0.04688 2 -1.13 0.3766 Intercept 9 -0.6988 0.8275 2 -0.84 0.4873 i_motivate 9 0.02656 0.05126 2 0.52 0.6560 Intercept 10 0.3014 1.2952 2 0.23 0.8377 i_motivate 10 -0.00159 0.06788 2 -0.02 0.9835 Intercept 11 1.5304 0.5329 2 2.87 0.1029 i_motivate 11 -0.04067 0.03083 2 -1.32 0.3179 Intercept 12 -1.4500 0.7016 2 -2.07 0.1747 i_motivate 12 0.05874 0.04854 2 1.21 0.3498 Intercept 13 -0.9585 0.7628 2 -1.26 0.3358 i_motivate 13 0.06423 0.04084 2 1.57 0.2564 Intercept 14 0.6172 1.2511 2 0.49 0.6706 i_motivate 14 -0.00393 0.06584 2 -0.06 0.9579 Intercept 15 -0.1989 1.3656 2 -0.15 0.8976 i_motivate 15 -0.02350 0.06560 2 -0.36 0.7545 Intercept 16 0.4511 1.0639 2 0.42 0.7128 i_motivate 16 -0.01855 0.06168 2 -0.30 0.7920 Intercept 17 -0.1120 0.8695 2 -0.13 0.9093 i_motivate 17 0.001013 0.05295 2 0.02 0.9865 Intercept 18 0.5675 1.3435 2 0.42 0.7138 i_motivate 18 -0.03329 0.06346 2 -0.52 0.6522 Intercept 19 0.8193 0.6996 2 1.17 0.3622 i_motivate 19 -0.03484 0.04035 2 -0.86 0.4789 Intercept 20 1.0078 1.0698 2 0.94 0.4456 i_motivate 20 -0.02770 0.06353 2 -0.44 0.7054 Intercept 21 0.7928 0.8733 2 0.91 0.4598 i_motivate 21 -0.03261 0.05463 2 -0.60 0.6111 Intercept 22 -0.3963 1.1836 2 -0.33 0.7696 i_motivate 22 0.03606 0.06337 2 0.57 0.6267 Intercept 23 0.3048 0.9255 2 0.33 0.7732 i_motivate 23 -0.00941 0.04915 2 -0.19 0.8658 Intercept 24 -0.2240 0.6001 2 -0.37 0.7448 i_motivate 24 -0.02475 0.03871 2 -0.64 0.5881 The SAS System 12 13:31 Thursday, January 12, 2012 The Mixed Procedure Solution for Random Effects Std Err Effect dyad Estimate Pred DF t Value Pr > |t| Intercept 25 -0.1554 1.2525 2 -0.12 0.9126 i_motivate 25 0.007217 0.06661 2 0.11 0.9236 Intercept 26 -0.07723 1.3658 2 -0.06 0.9601 i_motivate 26 0.006625 0.06567 2 0.10 0.9288 Intercept 27 0.001963 1.3138 2 0.00 0.9989 i_motivate 27 -0.00309 0.06356 2 -0.05 0.9656 Intercept 28 -2.5071 0.7303 2 -3.43 0.0754 i_motivate 28 0.08223 0.04258 2 1.93 0.1932 Intercept 29 -0.1769 1.2876 2 -0.14 0.9033 i_motivate 29 -0.00293 0.06766 2 -0.04 0.9694 Intercept 30 -1.4032 0.6599 2 -2.13 0.1673 i_motivate 30 0.08847 0.03642 2 2.43 0.1358 Intercept 31 1.9734 0.9999 2 1.97 0.1872 i_motivate 31 -0.06124 0.05820 2 -1.05 0.4031 Intercept 32 -0.1210 1.2761 2 -0.09 0.9331 i_motivate 32 -0.03260 0.06588 2 -0.49 0.6697 Intercept 33 0.6256 1.1568 2 0.54 0.6428 i_motivate 33 -0.01964 0.06390 2 -0.31 0.7877 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F i_motivate 1 30 0.43 0.5185 d_motivate_lo 1 2 0.45 0.5709 d_cohesion 1 2 12.17 0.0732 The SAS System 13 13:31 Thursday, January 12, 2012 The Mixed Procedure Model Information Data Set WORK.DYAD Dependent Variable i_perform Covariance Structure Unstructured Subject Effect dyad Estimation Method REML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Containment Class Level Information Class Levels Values dyad 33 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 Dimensions Covariance Parameters 4 Columns in X 4 Columns in Z Per Subject 2 Subjects 33 Max Obs Per Subject 2 Number of Observations Number of Observations Read 66 Number of Observations Used 66 Number of Observations Not Used 0 Iteration History Iteration Evaluations -2 Res Log Like Criterion 0 1 157.86674887 1 3 138.59025257 0.05684851 2 1 137.70099966 0.02095272 3 1 137.39899067 0.00404011 4 1 137.34546856 0.00022216 5 1 137.34276576 0.00000090 6 1 137.34275521 0.00000000 The SAS System 14 13:31 Thursday, January 12, 2012 The Mixed Procedure Convergence criteria met. Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr Z UN(1,1) dyad 1.9087 1.1265 1.69 0.0451 UN(2,1) dyad -0.08694 0.06433 -1.35 0.1765 UN(2,2) dyad 0.004614 0.003822 1.21 0.1136 Residual 0.1456 0.05354 2.72 0.0033 Fit Statistics -2 Res Log Likelihood 137.3 AIC (smaller is better) 145.3 AICC (smaller is better) 146.0 BIC (smaller is better) 151.3 Null Model Likelihood Ratio Test DF Chi-Square Pr > ChiSq 3 20.52 0.0001 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept -0.1844 1.0817 31 -0.17 0.8657 i_motivate 0.01582 0.02421 30 0.65 0.5185 d_motivate_hi 0.02633 0.03919 1 0.67 0.6234 d_cohesion 0.9010 0.2583 1 3.49 0.1777 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F i_motivate 1 30 0.43 0.5185 d_motivate_hi 1 1 0.45 0.6234 d_cohesion 1 1 12.17 0.1777