> data [[1]] GCA1 GCA2 SCA1 SCA2 SCA3 SD1 SD2 CL1 CL2 ES1 ES2 CE1 CE2 NPO TR GCA1 1.00 0.77 0.22 0.20 0.08 0.37 0.26 0.10 0.12 0.07 0.06 -0.28 -0.47 0.16 0.14 GCA2 0.77 1.00 0.25 0.21 0.08 0.33 0.25 0.12 0.15 0.07 0.05 -0.28 -0.41 0.15 0.12 SCA1 0.22 0.25 1.00 0.54 0.31 0.34 0.35 0.27 0.28 0.26 0.27 -0.09 -0.18 0.10 0.15 SCA2 0.20 0.21 0.54 1.00 0.40 0.42 0.42 0.21 0.17 0.14 0.12 0.04 -0.08 -0.05 0.01 SCA3 0.08 0.08 0.31 0.40 1.00 0.18 0.24 0.11 0.08 0.13 0.12 -0.02 -0.07 0.09 0.10 SD1 0.37 0.33 0.34 0.42 0.18 1.00 0.83 0.24 0.19 0.13 0.11 -0.09 -0.28 0.11 0.23 SD2 0.26 0.25 0.35 0.42 0.24 0.83 1.00 0.23 0.16 0.14 0.11 -0.06 -0.21 0.15 0.28 CL1 0.10 0.12 0.27 0.21 0.11 0.24 0.23 1.00 0.86 0.44 0.45 0.03 -0.07 0.02 0.18 CL2 0.12 0.15 0.28 0.17 0.08 0.19 0.16 0.86 1.00 0.46 0.46 0.02 -0.07 -0.02 0.11 ES1 0.07 0.07 0.26 0.14 0.13 0.13 0.14 0.44 0.46 1.00 0.93 0.07 -0.04 -0.07 0.01 ES2 0.06 0.05 0.27 0.12 0.12 0.11 0.11 0.45 0.46 0.93 1.00 0.08 -0.01 -0.11 -0.01 CE1 -0.28 -0.28 -0.09 0.04 -0.02 -0.09 -0.06 0.03 0.02 0.07 0.08 1.00 0.70 -0.35 -0.17 CE2 -0.47 -0.41 -0.18 -0.08 -0.07 -0.28 -0.21 -0.07 -0.07 -0.04 -0.01 0.70 1.00 -0.40 -0.26 NPO 0.16 0.15 0.10 -0.05 0.09 0.11 0.15 0.02 -0.02 -0.07 -0.11 -0.35 -0.40 1.00 0.69 TR 0.14 0.12 0.15 0.01 0.10 0.23 0.28 0.18 0.11 0.01 -0.01 -0.17 -0.26 0.69 1.00 [[2]] GCA1 GCA2 SCA1 SCA2 SCA3 SD1 SD2 CL1 CL2 ES1 ES2 CE1 CE2 NPO TR GCA1 1.00 0.86 0.19 0.16 0.24 0.50 0.52 0.33 0.18 0.05 -0.01 -0.46 -0.42 0.37 0.36 GCA2 0.86 1.00 0.22 0.21 0.22 0.49 0.49 0.24 0.10 0.06 -0.06 -0.38 -0.39 0.33 0.32 SCA1 0.19 0.22 1.00 0.41 0.42 0.15 0.14 0.21 0.27 0.21 0.23 -0.01 -0.01 -0.16 -0.07 SCA2 0.16 0.21 0.41 1.00 0.42 0.24 0.16 0.20 0.30 0.16 0.25 0.01 0.01 -0.09 -0.02 SCA3 0.24 0.22 0.42 0.42 1.00 0.25 0.22 0.28 0.27 0.06 0.07 -0.15 -0.15 -0.03 0.00 SD1 0.50 0.49 0.15 0.24 0.25 1.00 0.78 0.37 0.22 0.28 0.19 -0.36 -0.37 0.26 0.37 SD2 0.52 0.49 0.14 0.16 0.22 0.78 1.00 0.44 0.34 0.21 0.12 -0.41 -0.42 0.32 0.37 CL1 0.33 0.24 0.21 0.20 0.28 0.37 0.44 1.00 0.81 0.34 0.27 -0.20 -0.22 0.18 0.32 CL2 0.18 0.10 0.27 0.30 0.27 0.22 0.34 0.81 1.00 0.35 0.31 -0.10 -0.10 0.09 0.21 ES1 0.05 0.06 0.21 0.16 0.06 0.28 0.21 0.34 0.35 1.00 0.84 0.04 0.02 -0.05 0.04 ES2 -0.01 -0.06 0.23 0.25 0.07 0.19 0.12 0.27 0.31 0.84 1.00 0.10 0.01 -0.11 -0.02 CE1 -0.46 -0.38 -0.01 0.01 -0.15 -0.36 -0.41 -0.20 -0.10 0.04 0.10 1.00 0.89 -0.56 -0.43 CE2 -0.42 -0.39 -0.01 0.01 -0.15 -0.37 -0.42 -0.22 -0.10 0.02 0.01 0.89 1.00 -0.46 -0.40 NPO 0.37 0.33 -0.16 -0.09 -0.03 0.26 0.32 0.18 0.09 -0.05 -0.11 -0.56 -0.46 1.00 0.74 TR 0.36 0.32 -0.07 -0.02 0.00 0.37 0.37 0.32 0.21 0.04 -0.02 -0.43 -0.40 0.74 1.00 > n <- c(276, 155) > summary(cor) Call: tssem1FEM(my.df = my.df, n = n, cor.analysis = cor.analysis, model.name = model.name, cluster = cluster, suppressWarnings = suppressWarnings) Coefficients: Estimate Std.Error z value Pr(>|z|) S[1,2] 0.80763015 0.01692353 47.7223 < 2.2e-16 *** S[1,3] 0.20795871 0.04620241 4.5010 6.762e-06 *** S[1,4] 0.18425116 0.04665044 3.9496 7.828e-05 *** S[1,5] 0.14233174 0.04742686 3.0011 0.0026903 ** S[1,6] 0.41838277 0.03992471 10.4793 < 2.2e-16 *** S[1,7] 0.35809635 0.04240032 8.4456 < 2.2e-16 *** S[1,8] 0.18600006 0.04680938 3.9736 7.081e-05 *** S[1,9] 0.14153570 0.04732834 2.9905 0.0027852 ** S[1,10] 0.06240812 0.04809426 1.2976 0.1944176 S[1,11] 0.03557972 0.04823481 0.7376 0.4607358 S[1,12] -0.35869371 0.04223106 -8.4936 < 2.2e-16 *** S[1,13] -0.44777194 0.03861984 -11.5943 < 2.2e-16 *** S[1,14] 0.24617058 0.04554740 5.4047 6.491e-08 *** S[1,15] 0.22852646 0.04597003 4.9712 6.654e-07 *** S[2,3] 0.23791059 0.04555927 5.2220 1.770e-07 *** S[2,4] 0.20930914 0.04617008 4.5334 5.803e-06 *** S[2,5] 0.13444348 0.04750318 2.8302 0.0046519 ** S[2,6] 0.38984302 0.04107054 9.4920 < 2.2e-16 *** S[2,7] 0.34040197 0.04294704 7.9261 2.220e-15 *** S[2,8] 0.16456766 0.04702713 3.4994 0.0004663 *** S[2,9] 0.13090365 0.04746446 2.7579 0.0058169 ** S[2,10] 0.06581469 0.04807240 1.3691 0.1709760 S[2,11] 0.01220964 0.04831181 0.2527 0.8004802 S[2,12] -0.32353085 0.04327678 -7.4759 7.661e-14 *** S[2,13] -0.40093502 0.04052665 -9.8931 < 2.2e-16 *** S[2,14] 0.22374451 0.04600354 4.8636 1.152e-06 *** S[2,15] 0.20035945 0.04651392 4.3075 1.651e-05 *** S[3,4] 0.49569324 0.03652795 13.5702 < 2.2e-16 *** S[3,5] 0.34876788 0.04247915 8.2103 2.220e-16 *** S[3,6] 0.27463208 0.04479598 6.1307 8.748e-10 *** S[3,7] 0.27777803 0.04475218 6.2070 5.400e-10 *** S[3,8] 0.24961499 0.04529042 5.5114 3.559e-08 *** S[3,9] 0.27661300 0.04459003 6.2035 5.523e-10 *** S[3,10] 0.24395829 0.04542737 5.3703 7.861e-08 *** S[3,11] 0.25699437 0.04510834 5.6973 1.217e-08 *** S[3,12] -0.05763193 0.04815009 -1.1969 0.2313368 S[3,13] -0.11148167 0.04781048 -2.3317 0.0197143 * S[3,14] 0.00327475 0.04857689 0.0674 0.9462523 S[3,15] 0.06969203 0.04825884 1.4441 0.1487025 S[4,5] 0.40688582 0.04029379 10.0980 < 2.2e-16 *** S[4,6] 0.35840971 0.04222562 8.4880 < 2.2e-16 *** S[4,7] 0.33107402 0.04329445 7.6470 2.065e-14 *** S[4,8] 0.20662184 0.04622256 4.4702 7.816e-06 *** S[4,9] 0.21307500 0.04615815 4.6162 3.908e-06 *** S[4,10] 0.14574531 0.04726159 3.0838 0.0020437 ** S[4,11] 0.15933555 0.04711479 3.3819 0.0007200 *** S[4,12] 0.02786445 0.04824809 0.5775 0.5635853 S[4,13] -0.04399079 0.04822271 -0.9122 0.3616413 S[4,14] -0.06466077 0.04808495 -1.3447 0.1787158 S[4,15] -0.00088083 0.04828368 -0.0182 0.9854452 S[5,6] 0.20478129 0.04627758 4.4251 9.641e-06 *** S[5,7] 0.23286607 0.04566639 5.0993 3.409e-07 *** S[5,8] 0.16945448 0.04701902 3.6040 0.0003134 *** S[5,9] 0.14519736 0.04741525 3.0623 0.0021968 ** S[5,10] 0.10729272 0.04775126 2.2469 0.0246459 * S[5,11] 0.10364859 0.04777822 2.1694 0.0300547 * S[5,12] -0.07303913 0.04810839 -1.5182 0.1289589 S[5,13] -0.10231246 0.04781006 -2.1400 0.0323566 * S[5,14] 0.04401872 0.04825246 0.9123 0.3616326 S[5,15] 0.06243121 0.04813781 1.2969 0.1946564 S[6,7] 0.81273759 0.01642580 49.4793 < 2.2e-16 *** S[6,8] 0.28431735 0.04443887 6.3979 1.575e-10 *** S[6,9] 0.19999228 0.04635271 4.3146 1.599e-05 *** S[6,10] 0.17574756 0.04685905 3.7506 0.0001764 *** S[6,11] 0.13429450 0.04743014 2.8314 0.0046342 ** S[6,12] -0.19690339 0.04670608 -4.2158 2.489e-05 *** S[6,13] -0.31393434 0.04357785 -7.2040 5.849e-13 *** S[6,14] 0.16572004 0.04704100 3.5229 0.0004269 *** S[6,15] 0.28098361 0.04455063 6.3071 2.844e-10 *** S[7,8] 0.30157060 0.04405631 6.8451 7.641e-12 *** S[7,9] 0.22017802 0.04605516 4.7807 1.746e-06 *** S[7,10] 0.16110643 0.04704490 3.4245 0.0006159 *** S[7,11] 0.11275257 0.04766915 2.3653 0.0180147 * S[7,12] -0.19890793 0.04688483 -4.2425 2.211e-05 *** S[7,13] -0.29203500 0.04437121 -6.5816 4.653e-11 *** S[7,14] 0.21307992 0.04620687 4.6114 3.999e-06 *** S[7,15] 0.31263476 0.04359898 7.1707 7.463e-13 *** S[8,9] 0.84340527 0.01398158 60.3226 < 2.2e-16 *** S[8,10] 0.40861065 0.04026983 10.1468 < 2.2e-16 *** S[8,11] 0.39427300 0.04090271 9.6393 < 2.2e-16 *** S[8,12] -0.06065429 0.04830440 -1.2557 0.2092364 S[8,13] -0.12831036 0.04757396 -2.6971 0.0069952 ** S[8,14] 0.07883321 0.04807337 1.6399 0.1010359 S[8,15] 0.23030020 0.04579694 5.0287 4.938e-07 *** S[9,10] 0.42651875 0.03955307 10.7835 < 2.2e-16 *** S[9,11] 0.41458006 0.04007381 10.3454 < 2.2e-16 *** S[9,12] -0.02649232 0.04830216 -0.5485 0.5833687 S[9,13] -0.08089816 0.04797096 -1.6864 0.0917190 . S[9,14] 0.01979533 0.04830472 0.4098 0.6819518 S[9,15] 0.14519965 0.04730000 3.0698 0.0021423 ** S[10,11] 0.90533272 0.00888985 101.8389 < 2.2e-16 *** S[10,12] 0.05805376 0.04812375 1.2063 0.2276852 S[10,13] -0.01803567 0.04827758 -0.3736 0.7087147 S[10,14] -0.06271246 0.04809021 -1.3041 0.1922135 S[10,15] 0.01969806 0.04826197 0.4081 0.6831644 S[11,12] 0.08560721 0.04793202 1.7860 0.0740972 . S[11,13] -0.00273602 0.04828176 -0.0567 0.9548098 S[11,14] -0.10898617 0.04770734 -2.2845 0.0223437 * S[11,15] -0.01318633 0.04826991 -0.2732 0.7847155 S[12,13] 0.78703844 0.01895628 41.5186 < 2.2e-16 *** S[12,14] -0.43966788 0.03921078 -11.2129 < 2.2e-16 *** S[12,15] -0.27917945 0.04484269 -6.2258 4.793e-10 *** S[13,14] -0.42511464 0.03958647 -10.7389 < 2.2e-16 *** S[13,15] -0.31825455 0.04349511 -7.3170 2.536e-13 *** S[14,15] 0.70965382 0.02399685 29.5728 < 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Goodness-of-fit indices: Value Sample size 431.0000 Chi-square of target model 250.3566 DF of target model 105.0000 p value of target model 0.0000 Chi-square of independence model 3992.2522 DF of independence model 210.0000 RMSEA 0.0802 SRMR 0.0704 TLI 0.9231 CFI 0.9616 AIC 40.3566 BIC -386.5847 OpenMx status: 0 ("0" and "1": considered fine; other values indicate problems) > A FullMatrix 'A' @labels [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [1,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_GCA1" NA NA NA NA NA NA [2,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_GCA2" NA NA NA NA NA NA [3,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_SCA1" NA NA NA NA NA [4,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_SCA2" NA NA NA NA NA [5,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_SCA3" NA NA NA NA NA [6,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_SD1" NA NA NA NA [7,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_SD2" NA NA NA NA [8,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_CL1" NA NA [9,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_CL2" NA NA [10,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_ES1" NA [11,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_ES2" NA [12,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_CE1" [13,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "L_CE2" [14,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [15,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [16,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "SOF1" NA NA NA [17,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "SOF2" NA NA NA [18,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "SOF3" NA NA NA [19,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "ESLA_LCL" NA "ESLA_LCE" [20,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA "LES_LCL" NA [21,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [22,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [23,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [,23] [1,] NA [2,] NA [3,] NA [4,] NA [5,] NA [6,] NA [7,] NA [8,] NA [9,] NA [10,] NA [11,] NA [12,] NA [13,] NA [14,] "L_NPO1" [15,] "L_TR2" [16,] NA [17,] NA [18,] NA [19,] NA [20,] NA [21,] NA [22,] "LCE_SCL" [23,] NA @values [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.9 0.0 0.0 0.0 0.00 0.0 0.0 0.00 [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.9 0.0 0.0 0.0 0.00 0.0 0.0 0.00 [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.7 0.0 0.0 0.00 0.0 0.0 0.00 [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.8 0.0 0.0 0.00 0.0 0.0 0.00 [5,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.5 0.0 0.0 0.00 0.0 0.0 0.00 [6,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.9 0.0 0.00 0.0 0.0 0.00 [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.9 0.0 0.00 0.0 0.0 0.00 [8,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.90 0.0 0.0 0.00 [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.90 0.0 0.0 0.00 [10,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.9 0.0 0.00 [11,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.9 0.0 0.00 [12,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.0 0.9 0.00 [13,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.0 0.9 0.00 [14,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.90 [15,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.90 [16,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.6 0.00 0.0 0.0 0.00 [17,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.8 0.00 0.0 0.0 0.00 [18,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.5 0.00 0.0 0.0 0.00 [19,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.35 0.0 -0.4 0.00 [20,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.5 0.0 0.00 [21,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.00 [22,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 -0.45 [23,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.00 @free [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [1,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [2,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [3,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE [4,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE [5,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE [6,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE [7,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE [8,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE [9,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE [10,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE [11,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE [12,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE [13,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE [14,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE [15,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE [16,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE [17,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE [18,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE [19,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE FALSE [20,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE [21,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [22,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE [23,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE @lbound: No lower bounds assigned. @ubound: No upper bounds assigned. > S FullMatrix 'S' @labels [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [1,] "er1" NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [2,] NA "er2" NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [3,] NA NA "er3" NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [4,] NA NA NA "er4" NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [5,] NA NA NA NA "er5" NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [6,] NA NA NA NA NA "er6" NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [7,] NA NA NA NA NA NA "er7" NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [8,] NA NA NA NA NA NA NA "er8" NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [9,] NA NA NA NA NA NA NA NA "er9" NA NA NA NA NA NA NA NA NA NA NA NA NA NA [10,] NA NA NA NA NA NA NA NA NA "er10" NA NA NA NA NA NA NA NA NA NA NA NA NA [11,] NA NA NA NA NA NA NA NA NA NA "er11" NA NA NA NA NA NA NA NA NA NA NA NA [12,] NA NA NA NA NA NA NA NA NA NA NA "er12" NA NA NA NA NA NA NA NA NA NA NA [13,] NA NA NA NA NA NA NA NA NA NA NA NA "er13" NA NA NA NA NA NA NA NA NA NA [14,] NA NA NA NA NA NA NA NA NA NA NA NA NA "er14" NA NA NA NA NA NA NA NA NA [15,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA "er15" NA NA NA NA NA NA NA NA [16,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [17,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [18,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [19,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [20,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [21,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [22,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA [23,] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA @values [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [1,] 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [2,] 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [3,] 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [4,] 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [5,] 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [6,] 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [7,] 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [8,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [9,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [10,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [11,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [12,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0 0 0 0 0 0 0 0 [13,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0 0 0 0 0 0 0 0 [14,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0 0 0 0 0 0 0 0 [15,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0 0 0 0 0 0 0 0 [16,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1 0 0 0 0 0 0 0 [17,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 1 0 0 0 0 0 0 [18,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 1 0 0 0 0 0 [19,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 1 0 0 0 0 [20,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 1 0 0 0 [21,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 1 0 0 [22,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 1 0 [23,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0 0 0 0 0 1 @free [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [1,] TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [2,] FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [3,] FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [4,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [5,] FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [6,] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [7,] FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [8,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [9,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [10,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [11,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [12,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [13,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [14,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [15,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [16,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [17,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [18,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [19,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [20,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [21,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [22,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE [23,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE @lbound: No lower bounds assigned. @ubound: No upper bounds assigned. > F1 FullMatrix 'F1' @labels: No labels assigned. @values [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [1,] 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [2,] 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [3,] 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [4,] 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [5,] 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [6,] 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [7,] 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [8,] 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [9,] 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [10,] 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 [11,] 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 [12,] 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 [13,] 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 [14,] 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 [15,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 @free: No free parameters. @lbound: No lower bounds assigned. @ubound: No upper bounds assigned. > sem <- tssem2(cor, Amatrix = A, Smatrix = S, Fmatrix = F1, diag.constraint = TRUE, intervals = "LB") > summary(sem) Call: wls(Cov = tssem1.obj$pooledS, asyCov = tssem1.obj$acovS, n = tssem1.obj$total.n, Amatrix = Amatrix, Smatrix = Smatrix, Fmatrix = Fmatrix, diag.constraints = diag.constraints, cor.analysis = cor.analysis, intervals.type = intervals.type, mx.algebras = mx.algebras, model.name = model.name, suppressWarnings = suppressWarnings) 95% confidence intervals: Likelihood-based statistic Coefficients: Estimate Std.Error lbound ubound z value Pr(>|z|) Amatrix[1,16] 0.626850 NA 0.532694 0.708515 NA NA Amatrix[2,16] 0.597643 NA 0.511658 0.670011 NA NA Amatrix[3,17] 0.506508 NA 0.424227 0.586717 NA NA Amatrix[4,17] 0.578516 NA 0.482941 0.670680 NA NA Amatrix[5,17] 0.409358 NA 0.329086 0.491831 NA NA Amatrix[6,18] 0.624439 NA 0.526810 0.709824 NA NA Amatrix[7,18] 0.579584 NA 0.495192 0.649207 NA NA Amatrix[8,20] 0.827564 NA 0.772197 0.888755 NA NA Amatrix[9,20] 0.804422 NA 0.754789 0.858942 NA NA Amatrix[10,21] 0.975157 NA 0.934461 1.018018 NA NA Amatrix[11,21] 0.933795 NA 0.892702 0.975030 NA NA Amatrix[12,22] 0.756539 NA 0.707351 0.807736 NA NA Amatrix[13,22] 0.849831 NA 0.790275 0.911816 NA NA Amatrix[14,23] 1.017221 NA 0.931227 1.135581 NA NA Amatrix[15,23] 0.716445 NA 0.628935 0.795260 NA NA Amatrix[16,19] 0.840740 NA 0.664512 1.104138 NA NA Amatrix[17,19] 0.656476 NA 0.473994 0.919587 NA NA Amatrix[18,19] 0.860476 NA 0.675736 1.135482 NA NA Amatrix[19,20] 0.326549 NA 0.209924 0.457558 NA NA Amatrix[19,22] -0.653931 NA -0.835938 -0.512173 NA NA Amatrix[20,21] 0.522445 NA 0.418540 0.640433 NA NA Amatrix[22,23] -0.485016 NA -0.613842 -0.369412 NA NA Smatrix[1,1] 0.144897 NA 0.061618 0.221746 NA NA Smatrix[2,2] 0.222726 NA 0.143354 0.298681 NA NA Smatrix[3,3] 0.559476 NA 0.453027 0.654781 NA NA Smatrix[4,4] 0.425320 NA 0.302538 0.534223 NA NA Smatrix[5,5] 0.712259 NA 0.617067 0.793952 NA NA Smatrix[6,6] 0.129679 NA 0.046200 0.205269 NA NA Smatrix[7,7] 0.250224 NA 0.172430 0.325753 NA NA Smatrix[8,8] 0.128206 NA 0.033826 0.213867 NA NA Smatrix[9,9] 0.176282 NA 0.086674 0.260576 NA NA Smatrix[10,10] 0.049069 NA -0.036397 0.126806 NA NA Smatrix[11,11] 0.128026 NA 0.049288 0.203105 NA NA Smatrix[12,12] 0.293009 NA 0.210271 0.372707 NA NA Smatrix[13,13] 0.107894 NA 0.017763 0.188686 NA NA Smatrix[14,14] -0.034739 NA -0.290071 0.132898 NA NA Smatrix[15,15] 0.486707 NA 0.367514 0.604466 NA NA Goodness-of-fit indices: Value Sample size 431.0000 Chi-square of target model 220.6344 DF of target model 83.0000 p value of target model 0.0000 Number of constraints imposed on "Smatrix" 15.0000 DF manually adjusted 0.0000 Chi-square of independence model 24140.1451 DF of independence model 105.0000 RMSEA 0.0621 SRMR 0.0879 TLI 0.9928 CFI 0.9943 AIC 54.6344 BIC -282.8526 OpenMx status1: 0 ("0" and "1": considered fine; other values indicate problems)