The SAS System 1 15:05 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 15:05 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 15:05 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 1 157.78389992 1 1 144.81183275 0.00000000 Convergence criteria met. The SAS System 4 15:05 Thursday, January 12, 2012 The Mixed Procedure Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr > Z Intercept dyad 0.3208 0.1162 2.76 0.0029 Residual 0.2305 0.05763 4.00 <.0001 Fit Statistics -2 Res Log Likelihood 144.8 AIC (smaller is better) 148.8 AICC (smaller is better) 149.0 BIC (smaller is better) 151.8 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 3.4908 0.3206 30 10.89 <.0001 i_motivate 0.02430 0.01824 32 1.33 0.1921 d_motivate_c 0.01071 0.04036 32 0.27 0.7925 d_cohesion_c 0.9191 0.2736 32 3.36 0.0020 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_c 1 32 0.07 0.7925 d_cohesion_c 1 32 11.29 0.0020 The SAS System 5 15:05 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 6 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 1 169.38366075 1 2 154.21154178 0.00037599 2 1 154.20300699 0.00000101 3 1 154.20298471 0.00000000 The SAS System 6 15:05 Thursday, January 12, 2012 The Mixed Procedure Convergence criteria met. Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr > Z Intercept dyad 0.3857 0.1363 2.83 0.0023 Residual 0.1982 0.05269 3.76 <.0001 Fit Statistics -2 Res Log Likelihood 154.2 AIC (smaller is better) 158.2 AICC (smaller is better) 158.4 BIC (smaller is better) 161.2 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 3.0138 0.4113 30 7.33 <.0001 i_motivate 0.04826 0.02155 30 2.24 0.0327 d_motivate_c -0.1913 0.1118 30 -1.71 0.0975 d_cohesion_c 2.1163 0.8298 30 2.55 0.0161 i_motivat*d_motivate 0.01088 0.005579 30 1.95 0.0606 i_motivat*d_cohesion -0.07282 0.04799 30 -1.52 0.1397 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F i_motivate 1 30 5.01 0.0327 d_motivate_c 1 30 2.93 0.0975 d_cohesion_c 1 30 6.50 0.0161 i_motivat*d_motivate 1 30 3.80 0.0606 i_motivat*d_cohesion 1 30 2.30 0.1397 The SAS System 7 15:05 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 6 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 1 169.38366075 1 2 154.21154178 0.00037599 2 1 154.20300699 0.00000101 3 1 154.20298471 0.00000000 The SAS System 8 15:05 Thursday, January 12, 2012 The Mixed Procedure Convergence criteria met. Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr > Z Intercept dyad 0.3857 0.1363 2.83 0.0023 Residual 0.1982 0.05269 3.76 <.0001 Fit Statistics -2 Res Log Likelihood 154.2 AIC (smaller is better) 158.2 AICC (smaller is better) 158.4 BIC (smaller is better) 161.2 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 3.7029 0.3105 30 11.93 <.0001 i_motivate 0.009062 0.01847 30 0.49 0.6273 d_motivate_chi -0.1913 0.1118 30 -1.71 0.0975 d_cohesion_c 2.1163 0.8298 30 2.55 0.0161 i_motivat*d_motivate 0.01088 0.005579 30 1.95 0.0606 i_motivat*d_cohesion -0.07282 0.04799 30 -1.52 0.1397 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F i_motivate 1 30 0.24 0.6273 d_motivate_chi 1 30 2.93 0.0975 d_cohesion_c 1 30 6.50 0.0161 i_motivat*d_motivate 1 30 3.80 0.0606 i_motivat*d_cohesion 1 30 2.30 0.1397 The SAS System 9 15:05 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 6 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 1 169.38366075 1 2 154.21154178 0.00037599 2 1 154.20300699 0.00000101 3 1 154.20298471 0.00000000 The SAS System 10 15:05 Thursday, January 12, 2012 The Mixed Procedure Convergence criteria met. Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr > Z Intercept dyad 0.3857 0.1363 2.83 0.0023 Residual 0.1982 0.05269 3.76 <.0001 Fit Statistics -2 Res Log Likelihood 154.2 AIC (smaller is better) 158.2 AICC (smaller is better) 158.4 BIC (smaller is better) 161.2 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 2.3247 0.7528 30 3.09 0.0043 i_motivate 0.08746 0.03736 30 2.34 0.0261 d_motivate_clo -0.1913 0.1118 30 -1.71 0.0975 d_cohesion_c 2.1163 0.8298 30 2.55 0.0161 i_motivat*d_motivate 0.01088 0.005579 30 1.95 0.0606 i_motivat*d_cohesion -0.07282 0.04799 30 -1.52 0.1397 Type 3 Tests of Fixed Effects Num Den Effect DF DF F Value Pr > F i_motivate 1 30 5.48 0.0261 d_motivate_clo 1 30 2.93 0.0975 d_cohesion_c 1 30 6.50 0.0161 i_motivat*d_motivate 1 30 3.80 0.0606 i_motivat*d_cohesion 1 30 2.30 0.1397