*running model on balanced data (3 male, 3 female students per school); *reading in balanced data; DATA balanced; infile 'C:\Documents and Settings\djbauer\My Documents\CSEM\Multilevel\file1.dat'; input school_id f3. ma1 f3. ma2 f3. ma3 f3. fe1 f3. fe2 f3. fe3 f3. tot_samp f3. class_size f3.; drop tot_samp; RUN; * rearranging for PROC MIXED; DATA balanced2; SET Balanced; Array l[6] ma1-ma3 fe1-fe3; DO i = 1 to 6; IF i < 4 THEN sex = 0; ELSE sex = 1; language = l[i]; output; END; drop i ma1-ma3 fe1-fe3; RUN; proc mixed data=balanced2 covtest method=ml; class school_id; model language = sex/solution ddfm=bw notest; random intercept sex/ type=un subject=school_id; run; The SAS System 13:57 Thursday, February 20, 2003 1 The Mixed Procedure Model Information Data Set WORK.BALANCED2 Dependent Variable language Covariance Structure Unstructured Subject Effect school_id Estimation Method ML Residual Variance Method Profile Fixed Effects SE Method Model-Based Degrees of Freedom Method Between-Within Class Level Information Class Levels Values school_id 116 1 2 4 5 7 8 9 10 11 12 14 15 16 17 18 19 20 22 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 49 50 51 52 53 54 55 56 57 58 59 60 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 78 79 80 81 82 83 84 85 86 89 90 91 92 94 95 96 97 99 100 101 102 103 104 105 106 109 110 111 112 113 114 115 116 118 119 120 121 122 123 124 125 126 127 128 129 130 131 Dimensions Covariance Parameters 4 Columns in X 2 Columns in Z Per Subject 2 Subjects 116 Max Obs Per Subject 6 Observations Used 696 Observations Not Used 0 Total Observations 696 Iteration History Iteration Evaluations -2 Log Like Criterion 0 1 5011.16607230 1 1 4947.43294268 0.00000000 The SAS System 13:57 Thursday, February 20, 2003 2 The Mixed Procedure Convergence criteria met. Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr Z UN(1,1) school_id 25.3271 6.0772 4.17 <.0001 UN(2,1) school_id -8.8214 5.1063 -1.73 0.0841 UN(2,2) school_id 4.5720 6.3784 0.72 0.2367 Residual 59.6279 3.9148 15.23 <.0001 Fit Statistics -2 Log Likelihood 4947.4 AIC (smaller is better) 4959.4 AICC (smaller is better) 4959.6 BIC (smaller is better) 4976.0 Null Model Likelihood Ratio Test DF Chi-Square Pr > ChiSq 3 63.73 <.0001 Solution for Fixed Effects Standard Effect Estimate Error DF t Value Pr > |t| Intercept 39.3333 0.6242 115 63.01 <.0001 sex 2.9253 0.6181 579 4.73 <.0001