DATE: 3/24/2004 TIME: 15:26 L I S R E L 8.54 BY Karl G. J”reskog & Dag S”rbom This program is published exclusively by Scientific Software International, Inc. 7383 N. Lincoln Avenue, Suite 100 Lincolnwood, IL 60712, U.S.A. Phone: (800)247-6113, (847)675-0720, Fax: (847)675-2140 Copyright by Scientific Software International, Inc., 1981-2002 Use of this program is subject to the terms specified in the Universal Copyright Convention. Website: www.ssicentral.com The following lines were read from file C:\lang\lang-a2r.ls8: ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 ! Natasja van Lang -- Current data ! Restrictions on correlations between latent variables ! to make that matrix PHI positive definite DA NI=12 NO=255 LA * `SB1n', `SB2n', `SB3n', `SB4n' `CC1n', `CC2vn', `CC3vn', `CC4n' `SD1n', `SD2n', `SD3n,' `SD4n' / CM FI= c:\lang\langn1.cov AC FI= c:\lang\langn1.acv MO NX=12 NK=3 PA LX * 1 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 1 LE * `so', `co', `st' / IR PH(2,1) < .9988 IR PH(3,1) < .5044 IR PH(3,2) < .4626 Path Diagram OU ME=ML RS PC MI SC ND=5 ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Number of Input Variables 12 Number of Y - Variables 0 Number of X - Variables 12 Number of ETA - Variables 0 Number of KSI - Variables 3 Number of Observations 255 ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Covariance Matrix `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- `SB1n' 1.55280 `SB2n' 0.97189 7.48720 `SB3n' 1.29090 1.84770 3.58560 `SB4n' 1.38570 2.12480 2.21070 3.35510 `CC1n' 1.51920 2.32540 2.54920 2.38830 6.59370 `CC2vn' 0.58149 0.90486 1.04480 0.90752 0.84501 1.75950 `CC3vn' 0.31411 0.68851 0.29690 0.60661 0.27737 0.45198 `CC4n' 0.58252 4.21140 1.08870 1.13070 1.46310 0.67524 `SD1n' 0.33709 0.37893 0.33242 0.31064 0.28695 0.23600 `SD2n' 0.26543 0.55530 0.32297 0.38150 0.28144 0.38404 `SD3n 0.35231 0.90727 0.55053 0.60854 0.40401 0.19558 `SD4n 0.21723 0.73159 0.52409 0.53983 0.50069 0.24294 Covariance Matrix `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- `CC3vn' 2.32450 `CC4n' 0.39007 3.37080 `SD1n' 0.65339 0.17678 1.36910 `SD2n' 0.65339 0.33426 0.31633 1.17220 `SD3n 0.51428 0.50618 0.38116 0.34494 1.39900 `SD4n 0.34113 0.44141 0.35016 0.25567 0.22811 1.02550 ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Parameter Specifications LAMBDA-X KSI 1 KSI 2 KSI 3 -------- -------- -------- `SB1n' 1 0 0 `SB2n' 2 0 0 `SB3n' 3 0 0 `SB4n' 4 0 0 `CC1n' 0 5 0 `CC2vn' 0 6 0 `CC3vn' 0 7 0 `CC4n' 0 8 0 `SD1n' 0 0 9 `SD2n' 0 0 10 `SD3n 0 0 11 `SD4n 0 0 12 PHI KSI 1 KSI 2 KSI 3 -------- -------- -------- KSI 1 0 KSI 2 13 0 KSI 3 14 15 0 THETA-DELTA `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- 16 17 18 19 20 21 THETA-DELTA `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- 22 23 24 25 26 27 ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Number of Iterations = 44 LISREL Estimates (Maximum Likelihood) LAMBDA-X KSI 1 KSI 2 KSI 3 -------- -------- -------- `SB1n' -0.85661 - - - - (0.06978) -12.27554 `SB2n' -1.53925 - - - - (0.18747) -8.21067 `SB3n' -1.41460 - - - - (0.09328) -15.16584 `SB4n' -1.45096 - - - - (0.09161) -15.83859 `CC1n' - - -1.60519 - - (0.16140) -9.94543 `CC2vn' - - -0.64452 - - (0.08165) -7.89412 `CC3vn' - - -0.36623 - - (0.11209) -3.26727 `CC4n' - - -0.93932 - - (0.13427) -6.99582 `SD1n' - - - - -0.59081 (0.08870) -6.66047 `SD2n' - - - - -0.51961 (0.08347) -6.22523 `SD3n - - - - -0.60943 (0.09914) -6.14745 `SD4n - - - - -0.51146 (0.08490) -6.02403 PHI KSI 1 KSI 2 KSI 3 -------- -------- -------- KSI 1 1.00000 KSI 2 0.99880 1.00000 (0.04679) 21.34657 KSI 3 0.50440 0.46260 1.00000 (0.07663) (0.09071) 6.58202 5.09970 THETA-DELTA `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- 0.79582 5.04302 1.52125 1.18326 3.94761 1.33289 (0.09213) (0.42474) (0.19519) (0.15829) (0.44139) (0.10798) 8.63813 11.87318 7.79379 7.47505 8.94366 12.34345 THETA-DELTA `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- 2.18676 2.46469 1.01110 0.89528 1.01808 0.75721 (0.22061) (0.24584) (0.13583) (0.10849) (0.13507) (0.09499) 9.91254 10.02553 7.44390 8.25233 7.53752 7.97173 Squared Multiple Correlations for X - Variables `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- 0.47972 0.31964 0.56812 0.64019 0.39493 0.23761 Squared Multiple Correlations for X - Variables `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- 0.05779 0.26362 0.25663 0.23170 0.26730 0.25676 Goodness of Fit Statistics Degrees of Freedom = 51 Minimum Fit Function Chi-Square = 378.57007 (P = 0.0) Normal Theory Weighted Least Squares Chi-Square = 302.74488 (P = 0.0) Satorra-Bentler Scaled Chi-Square = 264.13897 (P = 0.0) Chi-Square Corrected for Non-Normality = 245.94538 (P = 0.0) Estimated Non-centrality Parameter (NCP) = 213.13897 90 Percent Confidence Interval for NCP = (166.03011 ; 267.77290) Minimum Fit Function Value = 1.49043 Population Discrepancy Function Value (F0) = 0.83913 90 Percent Confidence Interval for F0 = (0.65366 ; 1.05422) Root Mean Square Error of Approximation (RMSEA) = 0.12827 90 Percent Confidence Interval for RMSEA = (0.11321 ; 0.14377) P-Value for Test of Close Fit (RMSEA < 0.05) = 0.00000 Expected Cross-Validation Index (ECVI) = 1.25252 90 Percent Confidence Interval for ECVI = (1.06705 ; 1.46761) ECVI for Saturated Model = 0.61417 ECVI for Independence Model = 6.27588 Chi-Square for Independence Model with 66 Degrees of Freedom = 1570.07431 Independence AIC = 1594.07431 Model AIC = 318.13897 Saturated AIC = 156.00000 Independence CAIC = 1648.56947 Model CAIC = 440.75308 Saturated CAIC = 510.21856 Normed Fit Index (NFI) = 0.83177 Non-Normed Fit Index (NNFI) = 0.81661 Parsimony Normed Fit Index (PNFI) = 0.64273 Comparative Fit Index (CFI) = 0.85829 Incremental Fit Index (IFI) = 0.85969 Relative Fit Index (RFI) = 0.78229 Critical N (CN) = 75.42026 Root Mean Square Residual (RMR) = 0.36007 Standardized RMR = 0.10361 Goodness of Fit Index (GFI) = 0.83193 Adjusted Goodness of Fit Index (AGFI) = 0.74295 Parsimony Goodness of Fit Index (PGFI) = 0.54395 ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Fitted Covariance Matrix `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- `SB1n' 1.52961 `SB2n' 1.31854 7.41231 `SB3n' 1.21176 2.17743 3.52235 `SB4n' 1.24291 2.23339 2.05254 3.28855 `CC1n' 1.37337 2.46782 2.26798 2.32627 6.52424 `CC2vn' 0.55144 0.99089 0.91065 0.93405 1.03458 1.74830 `CC3vn' 0.31334 0.56304 0.51745 0.53075 0.58787 0.23604 `CC4n' 0.80367 1.44411 1.32717 1.36128 1.50778 0.60541 `SD1n' 0.25527 0.45870 0.42156 0.43239 0.43871 0.17615 `SD2n' 0.22451 0.40342 0.37076 0.38029 0.38584 0.15492 `SD3n 0.26332 0.47316 0.43484 0.44602 0.45254 0.18170 `SD4n 0.22099 0.39710 0.36494 0.37432 0.37979 0.15249 Fitted Covariance Matrix `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- `CC3vn' 2.32088 `CC4n' 0.34401 3.34701 `SD1n' 0.10009 0.25673 1.36015 `SD2n' 0.08803 0.22579 0.30699 1.16528 `SD3n 0.10325 0.26482 0.36006 0.31667 1.38948 `SD4n 0.08665 0.22224 0.30218 0.26576 0.31170 1.01880 Fitted Residuals `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- `SB1n' 0.02319 `SB2n' -0.34665 0.07489 `SB3n' 0.07914 -0.32973 0.06325 `SB4n' 0.14279 -0.10859 0.15816 0.06655 `CC1n' 0.14583 -0.14242 0.28122 0.06203 0.06946 `CC2vn' 0.03005 -0.08603 0.13415 -0.02653 -0.18957 0.01120 `CC3vn' 0.00077 0.12547 -0.22055 0.07586 -0.31050 0.21594 `CC4n' -0.22115 2.76729 -0.23847 -0.23058 -0.04468 0.06983 `SD1n' 0.08182 -0.07977 -0.08914 -0.12175 -0.15176 0.05985 `SD2n' 0.04092 0.15188 -0.04779 0.00121 -0.10440 0.22912 `SD3n 0.08899 0.43411 0.11569 0.16252 -0.04853 0.01388 `SD4n -0.00376 0.33449 0.15915 0.16551 0.12090 0.09045 Fitted Residuals `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- `CC3vn' 0.00362 `CC4n' 0.04606 0.02379 `SD1n' 0.55330 -0.07995 0.00895 `SD2n' 0.56536 0.10847 0.00934 0.00692 `SD3n 0.41103 0.24136 0.02110 0.02827 0.00952 `SD4n 0.25448 0.21917 0.04798 -0.01009 -0.08359 0.00670 Summary Statistics for Fitted Residuals Smallest Fitted Residual = -0.34665 Median Fitted Residual = 0.03548 Largest Fitted Residual = 2.76729 Stemleaf Plot - 0|333222222111111111000000000000000000000000 0|111111111111111111122222222233344 0|66 1| 1| 2| 2|8 Standardized Residuals `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- `SB1n' - - `SB2n' -2.85353 - - `SB3n' - - -1.93961 - - `SB4n' 8.16539 -0.75397 - - - - `CC1n' 2.28560 -0.52294 4.15917 0.76207 - - `CC2vn' 0.98858 -0.53752 30.81322 - - - - - - `CC3vn' 0.00757 0.53374 -1.74769 1.01857 -2.43633 1.98500 `CC4n' -2.17395 8.76035 -2.21708 -2.29868 -0.22547 0.65973 `SD1n' 1.11944 -0.63965 -1.12576 -2.20544 -1.09809 0.78660 `SD2n' 0.65181 0.93346 -0.51146 0.01490 -0.76920 2.95248 `SD3n 1.25149 2.52233 1.11022 1.91997 -0.35574 0.16204 `SD4n -0.06545 2.13325 1.87419 2.25757 0.96486 1.38202 Standardized Residuals `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- `CC3vn' 0.02380 `CC4n' 0.29174 0.14675 `SD1n' 4.90005 -0.90697 0.27742 `SD2n' 4.83609 0.94360 0.26961 0.14229 `SD3n 3.50330 1.78426 0.37010 0.49733 0.14593 `SD4n 2.67406 1.92719 1.11619 -0.48277 -1.57041 0.41437 Summary Statistics for Standardized Residuals Smallest Standardized Residual = -2.85353 Median Standardized Residual = 0.21583 Largest Standardized Residual = 30.81322 Stemleaf Plot - 0|322222222111111111000000000000000000000000000 0|1111111111111112222222233344 0|5589 1| 1| 2| 2| 3|1 Largest Negative Standardized Residuals Residual for `SB2n' and `SB1n' -2.85353 Largest Positive Standardized Residuals Residual for `SB4n' and `SB1n' 8.16539 Residual for `CC1n' and `SB3n' 4.15917 Residual for `CC2vn' and `SB3n' 30.81322 Residual for `CC4n' and `SB2n' 8.76035 Residual for `SD1n' and `CC3vn' 4.90005 Residual for `SD2n' and `CC2vn' 2.95248 Residual for `SD2n' and `CC3vn' 4.83609 Residual for `SD3n and `CC3vn' 3.50330 Residual for `SD4n and `CC3vn' 2.67406 ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Qplot of Standardized Residuals 3.5.......................................................................... . .. . . . . . . . . . . . . . . . . . . . . . . . x . . . . . x . . x . . x . . * N . . x x x o . . x x . r . . * xx . m . . xxx . a . . * xx . l . . xx . . . xx* . Q . . ** . u . . x*x . a . . xx . n . . xx . t . x xx x . i . . x . l . xxxx . e . *. . s . x x x . . . xx . . . x . . . x . . . x . . . . . . x . . . . . . . . . . . . . . . . . . . . . . . -3.5.......................................................................... -3.5 3.5 Standardized Residuals ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Modification Indices and Expected Change Modification Indices for LAMBDA-X KSI 1 KSI 2 KSI 3 -------- -------- -------- `SB1n' - - 0.00033 0.02145 `SB2n' - - - - 1.93999 `SB3n' - - 0.00255 0.61964 `SB4n' - - 0.00665 0.24187 `CC1n' 0.03893 - - 3.64380 `CC2vn' - - - - 2.24122 `CC3vn' - - - - 56.70450 `CC4n' - - - - 1.94435 `SD1n' 1.68398 1.71723 - - `SD2n' 0.04179 0.04186 - - `SD3n 3.87851 3.77376 - - `SD4n 5.65895 5.56595 - - Expected Change for LAMBDA-X KSI 1 KSI 2 KSI 3 -------- -------- -------- `SB1n' - - 0.00418 -0.01517 `SB2n' - - - - -0.37970 `SB3n' - - -0.00841 0.11265 `SB4n' - - -0.03369 0.06661 `CC1n' 0.10001 - - 0.50190 `CC2vn' - - - - -0.20448 `CC3vn' - - - - -1.27224 `CC4n' - - - - -0.27371 `SD1n' 0.13163 0.13075 - - `SD2n' -0.02044 -0.01990 - - `SD3n -0.25352 -0.24028 - - `SD4n -0.26023 -0.24928 - - Standardized Expected Change for LAMBDA-X KSI 1 KSI 2 KSI 3 -------- -------- -------- `SB1n' - - 0.00418 -0.01517 `SB2n' - - - - -0.37970 `SB3n' - - -0.00841 0.11265 `SB4n' - - -0.03369 0.06661 `CC1n' 0.10001 - - 0.50190 `CC2vn' - - - - -0.20448 `CC3vn' - - - - -1.27224 `CC4n' - - - - -0.27371 `SD1n' 0.13163 0.13075 - - `SD2n' -0.02044 -0.01990 - - `SD3n -0.25352 -0.24028 - - `SD4n -0.26023 -0.24928 - - Completely Standardized Expected Change for LAMBDA-X KSI 1 KSI 2 KSI 3 -------- -------- -------- `SB1n' - - 0.00338 -0.01227 `SB2n' - - - - -0.13946 `SB3n' - - -0.00448 0.06002 `SB4n' - - -0.01858 0.03673 `CC1n' 0.03916 - - 0.19650 `CC2vn' - - - - -0.15465 `CC3vn' - - - - -0.83511 `CC4n' - - - - -0.14961 `SD1n' 0.11287 0.11211 - - `SD2n' -0.01893 -0.01844 - - `SD3n -0.21508 -0.20384 - - `SD4n -0.25781 -0.24697 - - Modification Indices for PHI Note: This matrix is diagonal. KSI 1 KSI 2 KSI 3 -------- -------- -------- 6.81427 14.53040 - - Expected Change for PHI Note: This matrix is diagonal. KSI 1 KSI 2 KSI 3 -------- -------- -------- -1.12213 -1.16689 - - Standardized Expected Change for PHI Note: This matrix is diagonal. KSI 1 KSI 2 KSI 3 -------- -------- -------- -1.12213 -1.16689 - - Modification Indices for THETA-DELTA `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- `SB1n' - - `SB2n' 13.02076 - - `SB3n' 0.68900 8.12822 - - `SB4n' 7.57254 2.43417 4.82628 - - `CC1n' 1.58917 0.62889 3.81493 0.00013 - - `CC2vn' 0.04216 0.60553 2.01532 0.96380 3.79357 - - `CC3vn' 0.11978 0.15930 7.11310 0.12996 3.73500 4.18099 `CC4n' 10.64805 186.82901 8.48894 11.49047 0.35076 0.28759 `SD1n' 3.79691 0.79196 0.49048 2.56440 0.25885 0.33496 `SD2n' 0.02445 0.12526 1.82056 0.70432 1.03691 7.91996 `SD3n 0.00740 3.15161 0.00000 0.39308 1.59720 1.65247 `SD4n 4.28395 1.58559 0.60810 0.66450 0.07197 0.00012 Modification Indices for THETA-DELTA `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- `CC3vn' - - `CC4n' 0.07033 - - `SD1n' 14.91023 1.35246 - - `SD2n' 18.44958 0.20240 0.00147 - - `SD3n 2.68850 1.48193 0.08608 0.26941 - - `SD4n 0.09640 1.50569 1.23986 0.21776 7.42399 - - Expected Change for THETA-DELTA `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- `SB1n' - - `SB2n' -0.52980 - - `SB3n' 0.08042 -0.61598 - - `SB4n' 0.27124 -0.31914 0.36664 - - `CC1n' 0.17692 -0.25056 0.40944 0.00224 - - `CC2vn' 0.01549 -0.13774 0.15793 -0.10136 -0.36139 - - `CC3vn' -0.03153 0.08737 -0.35072 0.04416 -0.38897 0.22893 `CC4n' -0.33199 3.35584 -0.44063 -0.47665 -0.15745 0.06952 `SD1n' 0.12781 -0.14080 -0.06593 -0.13964 -0.07385 0.04687 `SD2n' 0.00953 0.05214 -0.11824 -0.06796 -0.13731 0.21212 `SD3n 0.00569 0.28352 0.00017 0.05533 -0.18527 -0.10501 `SD4n -0.11762 0.17253 0.06376 0.06169 0.03374 -0.00075 Expected Change for THETA-DELTA `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- `CC3vn' - - `CC4n' 0.04057 - - `SD1n' 0.38925 -0.12870 - - `SD2n' 0.40348 0.04633 0.00356 - - `SD3n 0.16660 0.13594 0.02938 0.04796 - - `SD4n 0.02709 0.11759 0.09287 -0.03439 -0.24604 - - Completely Standardized Expected Change for THETA-DELTA `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- `SB1n' - - `SB2n' -0.15734 - - `SB3n' 0.03465 -0.12055 - - `SB4n' 0.12094 -0.06464 0.10773 - - `CC1n' 0.05600 -0.03603 0.08541 0.00048 - - `CC2vn' 0.00947 -0.03826 0.06364 -0.04227 -0.10700 - - `CC3vn' -0.01673 0.02106 -0.12267 0.01598 -0.09996 0.11365 `CC4n' -0.14673 0.67375 -0.12833 -0.14367 -0.03369 0.02874 `SD1n' 0.08861 -0.04435 -0.03012 -0.06603 -0.02479 0.03039 `SD2n' 0.00714 0.01774 -0.05836 -0.03472 -0.04980 0.14861 `SD3n 0.00390 0.08835 0.00008 0.02588 -0.06153 -0.06737 `SD4n -0.09422 0.06278 0.03366 0.03370 0.01309 -0.00056 Completely Standardized Expected Change for THETA-DELTA `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- `CC3vn' - - `CC4n' 0.01456 - - `SD1n' 0.21908 -0.06032 - - `SD2n' 0.24535 0.02346 0.00283 - - `SD3n 0.09277 0.06304 0.02137 0.03769 - - `SD4n 0.01762 0.06368 0.07890 -0.03156 -0.20680 - - Maximum Modification Index is 186.83 for Element ( 8, 2) of THETA-DELTA Covariance Matrix of Parameter Estimates LX 1,1 LX 2,1 LX 3,1 LX 4,1 LX 5,2 LX 6,2 -------- -------- -------- -------- -------- -------- LX 1,1 0.00487 LX 2,1 0.00000 0.03514 LX 3,1 0.00072 0.00309 0.00870 LX 4,1 0.00170 0.00247 0.00313 0.00839 LX 5,2 0.00208 0.00242 0.00295 0.00296 0.02605 LX 6,2 0.00019 0.00149 -0.00023 -0.00142 -0.00126 0.00667 LX 7,2 0.00014 0.00163 -0.00110 -0.00174 -0.00418 0.00321 LX 8,2 0.00011 0.02127 0.00116 0.00122 0.00349 0.00136 LX 9,3 0.00031 -0.00121 -0.00154 -0.00119 -0.00008 0.00054 LX 10,3 -0.00022 -0.00069 -0.00014 -0.00104 -0.00297 0.00125 LX 11,3 -0.00049 0.00457 0.00071 0.00050 -0.00104 -0.00060 LX 12,3 0.00036 0.00223 0.00127 0.00079 0.00158 -0.00059 PH 2,1 0.00016 0.00050 -0.00046 -0.00013 0.00294 0.00070 PH 3,1 -0.00057 -0.00193 -0.00049 0.00008 0.00091 -0.00083 PH 3,2 -0.00112 -0.00181 -0.00008 -0.00067 0.00137 -0.00078 TD 1,1 0.00270 -0.00288 0.00043 -0.00039 0.00080 0.00017 TD 2,2 0.00031 0.01481 -0.00663 -0.00585 -0.00266 0.00326 TD 3,3 -0.00153 0.00269 0.00926 0.00124 0.00038 -0.00031 TD 4,4 -0.00121 -0.00028 -0.00007 0.00435 -0.00182 0.00034 TD 5,5 0.00174 -0.00135 -0.00369 0.00054 0.03675 0.00272 TD 6,6 0.00016 -0.00063 -0.00071 -0.00179 0.00067 0.00454 TD 7,7 -0.00287 -0.00285 -0.00138 -0.00167 0.00401 -0.00030 TD 8,8 0.00004 0.00406 -0.00207 -0.00283 -0.00107 0.00048 TD 9,9 0.00095 0.00073 -0.00131 -0.00036 0.00087 0.00124 TD 10,10 0.00003 -0.00141 -0.00003 -0.00102 -0.00194 0.00086 TD 11,11 -0.00016 0.00463 0.00000 -0.00029 -0.00017 -0.00013 TD 12,12 0.00015 -0.00009 0.00036 0.00020 0.00089 -0.00017 Covariance Matrix of Parameter Estimates LX 7,2 LX 8,2 LX 9,3 LX 10,3 LX 11,3 LX 12,3 -------- -------- -------- -------- -------- -------- LX 7,2 0.01256 LX 8,2 0.00136 0.01803 LX 9,3 0.00182 -0.00085 0.00787 LX 10,3 0.00279 -0.00105 0.00009 0.00697 LX 11,3 -0.00025 0.00207 -0.00076 0.00070 0.00983 LX 12,3 -0.00077 0.00128 -0.00115 -0.00105 0.00003 0.00721 PH 2,1 0.00029 0.00167 0.00020 -0.00059 -0.00013 -0.00014 PH 3,1 -0.00225 -0.00130 0.00160 0.00058 -0.00039 -0.00013 PH 3,2 -0.00227 -0.00060 0.00170 -0.00040 -0.00061 -0.00015 TD 1,1 0.00033 -0.00210 0.00007 -0.00027 -0.00163 0.00084 TD 2,2 0.00575 0.01188 0.00380 -0.00028 0.00228 -0.00170 TD 3,3 -0.00121 0.00101 -0.00078 -0.00003 0.00110 0.00042 TD 4,4 0.00131 0.00096 0.00074 0.00039 0.00046 -0.00036 TD 5,5 -0.00145 0.00507 0.00192 -0.00394 -0.00234 -0.00005 TD 6,6 0.00303 0.00029 0.00137 0.00017 -0.00143 -0.00028 TD 7,7 -0.00689 -0.00073 -0.00194 -0.00298 -0.00312 0.00183 TD 8,8 0.00259 0.00255 0.00174 -0.00121 0.00093 -0.00183 TD 9,9 0.00103 0.00059 0.00585 0.00023 -0.00081 -0.00166 TD 10,10 0.00183 -0.00023 0.00029 0.00300 -0.00072 -0.00080 TD 11,11 0.00048 0.00231 -0.00229 0.00050 0.00549 -0.00008 TD 12,12 0.00012 -0.00044 -0.00175 -0.00043 -0.00152 0.00397 Covariance Matrix of Parameter Estimates PH 2,1 PH 3,1 PH 3,2 TD 1,1 TD 2,2 TD 3,3 -------- -------- -------- -------- -------- -------- PH 2,1 0.00219 PH 3,1 -0.00003 0.00587 PH 3,2 0.00040 0.00451 0.00823 TD 1,1 -0.00002 -0.00061 -0.00065 0.00849 TD 2,2 0.00336 -0.00013 -0.00033 0.00454 0.18040 TD 3,3 -0.00041 -0.00054 0.00046 -0.00050 0.00163 0.03810 TD 4,4 0.00091 -0.00052 -0.00071 0.00004 0.00270 -0.00084 TD 5,5 0.00912 -0.00070 0.00587 0.00559 0.01901 -0.00148 TD 6,6 0.00123 -0.00071 -0.00059 0.00023 0.00613 0.00021 TD 7,7 0.00058 0.00095 0.00203 0.00048 0.01049 0.00453 TD 8,8 0.00283 -0.00163 0.00045 0.00399 0.04706 0.00249 TD 9,9 -0.00051 0.00069 0.00106 0.00239 0.00057 -0.00180 TD 10,10 -0.00037 -0.00004 0.00089 0.00036 0.00172 0.00124 TD 11,11 0.00028 -0.00049 0.00032 -0.00020 0.00575 0.00195 TD 12,12 -0.00011 -0.00071 -0.00125 0.00062 -0.00233 -0.00069 Covariance Matrix of Parameter Estimates TD 4,4 TD 5,5 TD 6,6 TD 7,7 TD 8,8 TD 9,9 -------- -------- -------- -------- -------- -------- TD 4,4 0.02506 TD 5,5 0.00740 0.19482 TD 6,6 -0.00098 0.00456 0.01166 TD 7,7 0.00060 0.01090 0.00111 0.04867 TD 8,8 0.00190 0.01967 0.00220 0.00536 0.06044 TD 9,9 -0.00009 0.00500 0.00173 0.00036 0.00062 0.01845 TD 10,10 0.00097 0.00052 0.00035 0.00199 0.00312 0.00062 TD 11,11 -0.00079 0.00016 -0.00022 0.00045 0.00760 -0.00013 TD 12,12 -0.00119 -0.00052 -0.00020 0.00385 -0.00070 -0.00111 Covariance Matrix of Parameter Estimates TD 10,10 TD 11,11 TD 12,12 -------- -------- -------- TD 10,10 0.01177 TD 11,11 0.00106 0.01824 TD 12,12 -0.00054 0.00006 0.00902 ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Correlation Matrix of Parameter Estimates LX 1,1 LX 2,1 LX 3,1 LX 4,1 LX 5,2 LX 6,2 -------- -------- -------- -------- -------- -------- LX 1,1 1.00000 LX 2,1 0.00010 1.00000 LX 3,1 0.10996 0.17648 1.00000 LX 4,1 0.26670 0.14359 0.36646 1.00000 LX 5,2 0.18436 0.07995 0.19610 0.20006 1.00000 LX 6,2 0.03259 0.09718 -0.02985 -0.18974 -0.09595 1.00000 LX 7,2 0.01739 0.07772 -0.10554 -0.16920 -0.23113 0.35069 LX 8,2 0.01155 0.84506 0.09251 0.09928 0.16107 0.12440 LX 9,3 0.05078 -0.07279 -0.18618 -0.14682 -0.00563 0.07443 LX 10,3 -0.03767 -0.04389 -0.01758 -0.13626 -0.22055 0.18271 LX 11,3 -0.07033 0.24616 0.07688 0.05481 -0.06528 -0.07379 LX 12,3 0.06084 0.13981 0.16065 0.10183 0.11536 -0.08538 PH 2,1 0.05023 0.05656 -0.10444 -0.03088 0.38975 0.18404 PH 3,1 -0.10602 -0.13412 -0.06912 0.01095 0.07397 -0.13211 PH 3,2 -0.17744 -0.10656 -0.00907 -0.08014 0.09373 -0.10531 TD 1,1 0.41985 -0.16665 0.05050 -0.04655 0.05354 0.02239 TD 2,2 0.01056 0.18601 -0.16743 -0.15030 -0.03877 0.09413 TD 3,3 -0.11237 0.07352 0.50841 0.06934 0.01220 -0.01920 TD 4,4 -0.10933 -0.00938 -0.00483 0.30019 -0.07143 0.02608 TD 5,5 0.05637 -0.01631 -0.08972 0.01330 0.51581 0.07545 TD 6,6 0.02095 -0.03093 -0.07032 -0.18058 0.03834 0.51486 TD 7,7 -0.18633 -0.06899 -0.06723 -0.08268 0.11254 -0.01678 TD 8,8 0.00254 0.08799 -0.09040 -0.12583 -0.02699 0.02400 TD 9,9 0.10049 0.02873 -0.10327 -0.02876 0.03966 0.11166 TD 10,10 0.00408 -0.06949 -0.00291 -0.10213 -0.11053 0.09737 TD 11,11 -0.01743 0.18279 0.00004 -0.02332 -0.00775 -0.01181 TD 12,12 0.02334 -0.00494 0.04111 0.02318 0.05809 -0.02134 Correlation Matrix of Parameter Estimates LX 7,2 LX 8,2 LX 9,3 LX 10,3 LX 11,3 LX 12,3 -------- -------- -------- -------- -------- -------- LX 7,2 1.00000 LX 8,2 0.09016 1.00000 LX 9,3 0.18255 -0.07159 1.00000 LX 10,3 0.29798 -0.09389 0.01181 1.00000 LX 11,3 -0.02272 0.15542 -0.08591 0.08492 1.00000 LX 12,3 -0.08104 0.11241 -0.15331 -0.14809 0.00352 1.00000 PH 2,1 0.05457 0.26542 0.04843 -0.15148 -0.02834 -0.03450 PH 3,1 -0.26240 -0.12641 0.23506 0.09144 -0.05136 -0.02018 PH 3,2 -0.22281 -0.04939 0.21124 -0.05327 -0.06746 -0.02005 TD 1,1 0.03182 -0.16936 0.00916 -0.03525 -0.17852 0.10731 TD 2,2 0.12078 0.20840 0.10096 -0.00788 0.05417 -0.04724 TD 3,3 -0.05532 0.03862 -0.04533 -0.00172 0.05696 0.02524 TD 4,4 0.07365 0.04514 0.05263 0.02935 0.02946 -0.02687 TD 5,5 -0.02931 0.08555 0.04895 -0.10702 -0.05342 -0.00128 TD 6,6 0.24993 0.02002 0.14344 0.01907 -0.13342 -0.03036 TD 7,7 -0.27867 -0.02477 -0.09914 -0.16159 -0.14264 0.09752 TD 8,8 0.09390 0.07725 0.07992 -0.05885 0.03816 -0.08751 TD 9,9 0.06743 0.03251 0.48566 0.02031 -0.05994 -0.14363 TD 10,10 0.15076 -0.01580 0.03063 0.33136 -0.06722 -0.08647 TD 11,11 0.03192 0.12752 -0.19150 0.04400 0.41014 -0.00727 TD 12,12 0.01097 -0.03448 -0.20827 -0.05481 -0.16101 0.49279 Correlation Matrix of Parameter Estimates PH 2,1 PH 3,1 PH 3,2 TD 1,1 TD 2,2 TD 3,3 -------- -------- -------- -------- -------- -------- PH 2,1 1.00000 PH 3,1 -0.00923 1.00000 PH 3,2 0.09440 0.64888 1.00000 TD 1,1 -0.00543 -0.08638 -0.07821 1.00000 TD 2,2 0.16905 -0.00393 -0.00863 0.11612 1.00000 TD 3,3 -0.04529 -0.03630 0.02588 -0.02796 0.01962 1.00000 TD 4,4 0.12335 -0.04322 -0.04977 0.00255 0.04013 -0.02703 TD 5,5 0.44151 -0.02057 0.14668 0.13745 0.10137 -0.01718 TD 6,6 0.24395 -0.08557 -0.06025 0.02269 0.13363 0.00993 TD 7,7 0.05654 0.05628 0.10126 0.02357 0.11198 0.10521 TD 8,8 0.24623 -0.08656 0.02033 0.17602 0.45071 0.05189 TD 9,9 -0.08093 0.06645 0.08598 0.19073 0.00991 -0.06785 TD 10,10 -0.07219 -0.00434 0.09024 0.03625 0.03732 0.05856 TD 11,11 0.04499 -0.04706 0.02614 -0.01632 0.10028 0.07391 TD 12,12 -0.02440 -0.09811 -0.14511 0.07054 -0.05785 -0.03746 Correlation Matrix of Parameter Estimates TD 4,4 TD 5,5 TD 6,6 TD 7,7 TD 8,8 TD 9,9 -------- -------- -------- -------- -------- -------- TD 4,4 1.00000 TD 5,5 0.10585 1.00000 TD 6,6 -0.05733 0.09572 1.00000 TD 7,7 0.01705 0.11196 0.04641 1.00000 TD 8,8 0.04893 0.18130 0.08280 0.09878 1.00000 TD 9,9 -0.00420 0.08340 0.11821 0.01218 0.01860 1.00000 TD 10,10 0.05649 0.01089 0.02969 0.08326 0.11716 0.04237 TD 11,11 -0.03695 0.00275 -0.01536 0.01500 0.22894 -0.00732 TD 12,12 -0.07932 -0.01230 -0.01949 0.18364 -0.03006 -0.08622 Correlation Matrix of Parameter Estimates TD 10,10 TD 11,11 TD 12,12 -------- -------- -------- TD 10,10 1.00000 TD 11,11 0.07245 1.00000 TD 12,12 -0.05249 0.00461 1.00000 ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Standardized Solution LAMBDA-X KSI 1 KSI 2 KSI 3 -------- -------- -------- `SB1n' -0.85661 - - - - `SB2n' -1.53925 - - - - `SB3n' -1.41460 - - - - `SB4n' -1.45096 - - - - `CC1n' - - -1.60519 - - `CC2vn' - - -0.64452 - - `CC3vn' - - -0.36623 - - `CC4n' - - -0.93932 - - `SD1n' - - - - -0.59081 `SD2n' - - - - -0.51961 `SD3n - - - - -0.60943 `SD4n - - - - -0.51146 PHI KSI 1 KSI 2 KSI 3 -------- -------- -------- KSI 1 1.00000 KSI 2 0.99880 1.00000 KSI 3 0.50440 0.46260 1.00000 ! Restricted three-factor DSM model: Model A2R LANG-A2R.LS8 Completely Standardized Solution LAMBDA-X KSI 1 KSI 2 KSI 3 -------- -------- -------- `SB1n' -0.69262 - - - - `SB2n' -0.56537 - - - - `SB3n' -0.75373 - - - - `SB4n' -0.80012 - - - - `CC1n' - - -0.62844 - - `CC2vn' - - -0.48745 - - `CC3vn' - - -0.24040 - - `CC4n' - - -0.51343 - - `SD1n' - - - - -0.50659 `SD2n' - - - - -0.48135 `SD3n - - - - -0.51701 `SD4n - - - - -0.50672 PHI KSI 1 KSI 2 KSI 3 -------- -------- -------- KSI 1 1.00000 KSI 2 0.99880 1.00000 KSI 3 0.50440 0.46260 1.00000 THETA-DELTA `SB1n' `SB2n' `SB3n' `SB4n' `CC1n' `CC2vn' -------- -------- -------- -------- -------- -------- 0.52028 0.68036 0.43188 0.35981 0.60507 0.76239 THETA-DELTA `CC3vn' `CC4n' `SD1n' `SD2n' `SD3n `SD4n -------- -------- -------- -------- -------- -------- 0.94221 0.73638 0.74337 0.76830 0.73270 0.74324 Time used: 7.452 Seconds