* rearranging for multivariate PROC MIXED using loading estimates from SEM; * setting up control items for 2 factor model; * loadings fixed to SEM estimated values; DATA _null_; set new; file 'C:\Documents and Settings\djbauer\My Documents\CSEM\Multilevel\HSBdat\Mixed2.dat'; ly0 = 0; ly11 = 1; ly52 = 1; ly21 = .98355162; ly31 = 1.1367089; ly41 = 1.2730174; ly62 = .98200250; ly72 = .54685235; ly82 = .60928023; ly92 = .42765433; Array c1[30] c1n1-c1n30; Array c2[30] c2n1-c2n30; Array c3[30] c3n1-c3n30; Array c4[30] c4n1-c4n30; Array c5[30] c5n1-c5n30; Array c6[30] c6n1-c6n30; Array c7[30] c7n1-c7n30; Array c8[30] c8n1-c8n30; Array c9[30] c9n1-c9n30; Array s[30] sex1-sex30; DO i = 1 to 30; put c1[i] f10.8 ly11 f14.10 ly0 f14.10 s[i] f3. i f4. school_id f6.; put c2[i] f10.8 ly21 f14.10 ly0 f14.10 s[i] f3. i f4. school_id f6.; put c3[i] f10.8 ly31 f14.10 ly0 f14.10 s[i] f3. i f4. school_id f6.; put c4[i] f10.8 ly41 f14.10 ly0 f14.10 s[i] f3. i f4. school_id f6.; put c5[i] f10.8 ly0 f14.10 ly52 f14.10 s[i] f3. i f4. school_id f6.; put c6[i] f10.8 ly0 f14.10 ly62 f14.10 s[i] f3. i f4. school_id f6.; put c7[i] f10.8 ly0 f14.10 ly72 f14.10 s[i] f3. i f4. school_id f6.; put c8[i] f10.8 ly0 f14.10 ly82 f14.10 s[i] f3. i f4. school_id f6.; put c9[i] f10.8 ly0 f14.10 ly92 f14.10 s[i] f3. i f4. school_id f6.; END; RUN; DATA mixed; infile 'C:\Documents and Settings\djbauer\My Documents\CSEM\Multilevel\HSBdat\Mixed2.dat'; input control eta1 eta2 sex teach_id school_id; RUN; DATA mixed; set mixed; where control ne .; RUN; PROC MIXED data=mixed noclprint covtest method=ml; title 'multilevel CFA w/ free error variances, loadings fixed to SEM values'; class teach_id school_id; model control = /noint solution ddfm=bw; random eta1 eta2 /type=un sub=school_id; random eta1 eta2 /type=un sub=teach_id(school_id); repeated /type=un(1) sub=teach_id(school_id); RUN; multilevel CFA w/ free error variances, loadings fixed to SEM values 26 13:57 Thursday, February 20, 2003 The Mixed Procedure Model Information Data Set WORK.MIXED Dependent Variable control Covariance Structure Unstructured Subject Effects school_id, teach_id(school_id), teach_id(school_id) Estimation Method ML Residual Variance Method None Fixed Effects SE Method Model-Based Degrees of Freedom Method Between-Within Dimensions Covariance Parameters 51 Columns in X 0 Columns in Z Per Subject 62 Subjects 456 Max Obs Per Subject 270 Observations Used 92334 Observations Not Used 0 Total Observations 92334 Iteration History Iteration Evaluations -2 Log Like Criterion 0 1 304913.42794646 1 2 273813.46008283 0.00000390 2 1 273813.25270849 0.00000001 Convergence criteria met. Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr Z UN(1,1) school_id 0.2078 0.01677 12.39 <.0001 UN(2,1) school_id 0.1146 0.01220 9.39 <.0001 UN(2,2) school_id 0.1545 0.01323 11.67 <.0001 UN(1,1) teach_id(school_id) 0.5251 0.01134 46.32 <.0001 UN(2,1) teach_id(school_id) 0.2696 0.008798 30.65 <.0001 UN(2,2) teach_id(school_id) 0.6447 0.01274 50.62 <.0001 UN(1,1) teach_id(school_id) 1.2546 0.02036 61.62 <.0001 multilevel CFA w/ free error variances, loadings fixed to SEM values 27 13:57 Thursday, February 20, 2003 The Mixed Procedure Covariance Parameter Estimates Standard Z Cov Parm Subject Estimate Error Value Pr Z UN(2,1) teach_id(school_id) 0 . . . UN(2,2) teach_id(school_id) 1.4879 0.02352 63.27 <.0001 UN(3,1) teach_id(school_id) 0 . . . UN(3,2) teach_id(school_id) 0 . . . UN(3,3) teach_id(school_id) 1.3745 0.02296 59.88 <.0001 UN(4,1) teach_id(school_id) 0 . . . UN(4,2) teach_id(school_id) 0 . . . UN(4,3) teach_id(school_id) 0 . . . UN(4,4) teach_id(school_id) 1.0075 0.01956 51.51 <.0001 UN(5,1) teach_id(school_id) 0 . . . UN(5,2) teach_id(school_id) 0 . . . UN(5,3) teach_id(school_id) 0 . . . UN(5,4) teach_id(school_id) 0 . . . UN(5,5) teach_id(school_id) 0.9683 0.01655 58.50 <.0001 UN(6,1) teach_id(school_id) 0 . . . UN(6,2) teach_id(school_id) 0 . . . UN(6,3) teach_id(school_id) 0 . . . UN(6,4) teach_id(school_id) 0 . . . UN(6,5) teach_id(school_id) 0 . . . UN(6,6) teach_id(school_id) 0.5843 0.01152 50.72 <.0001 UN(7,1) teach_id(school_id) 0 . . . UN(7,2) teach_id(school_id) 0 . . . UN(7,3) teach_id(school_id) 0 . . . UN(7,4) teach_id(school_id) 0 . . . UN(7,5) teach_id(school_id) 0 . . . UN(7,6) teach_id(school_id) 0 . . . UN(7,7) teach_id(school_id) 0.3753 0.006156 60.96 <.0001 UN(8,1) teach_id(school_id) 0 . . . UN(8,2) teach_id(school_id) 0 . . . UN(8,3) teach_id(school_id) 0 . . . UN(8,4) teach_id(school_id) 0 . . . UN(8,5) teach_id(school_id) 0 . . . UN(8,6) teach_id(school_id) 0 . . . UN(8,7) teach_id(school_id) 0 . . . UN(8,8) teach_id(school_id) 1.0092 0.01516 66.59 <.0001 UN(9,1) teach_id(school_id) 0 . . . UN(9,2) teach_id(school_id) 0 . . . UN(9,3) teach_id(school_id) 0 . . . UN(9,4) teach_id(school_id) 0 . . . UN(9,5) teach_id(school_id) 0 . . . UN(9,6) teach_id(school_id) 0 . . . UN(9,7) teach_id(school_id) 0 . . . UN(9,8) teach_id(school_id) 0 . . . UN(9,9) teach_id(school_id) 0.4626 0.007097 65.18 <.0001 multilevel CFA w/ free error variances, loadings fixed to SEM values 28 13:57 Thursday, February 20, 2003 The Mixed Procedure Fit Statistics -2 Log Likelihood 273813.3 AIC (smaller is better) 273843.3 AICC (smaller is better) 273843.3 BIC (smaller is better) 273905.1 Null Model Likelihood Ratio Test DF Chi-Square Pr > ChiSq 14 31100.18 <.0001