C:\Users\user\Desktop\paper\paper10 Leader’s Political Skill, Knowledge Sharing, and Career Growth During Economic and Employment Uncertainty The Moderating Role of Job Insecurity\2.AMOS数据\直接假设.amw

Analysis Summary

Date and Time

Date: 2026年5月9日
Time: 22:47:18

Title

直接假设: 2026年5月9日 22:47

Groups

Group number 1 (Group number 1)

Notes for Group (Group number 1)

The model is recursive.
Sample size = 423

Variable Summary (Group number 1)

Your model contains the following variables (Group number 1)

Observed, endogenous variables
LPS1
LPS2
LPS3
LPS4
LPS5
LPS6
KS1
KS2
KS3
KS4
KS5
CG1
CG2
CG3
CG4
CG5
CG6
CG7
CG8
CG9
CG10
CG11
CG12
CG13
CG14
CG15
Unobserved, endogenous variables
F2KS
F3CG
Unobserved, exogenous variables
F1LPS
e1
e2
e3
e4
e5
e6
e7
e8
e9
e10
e11
e12
e13
e14
e15
e16
e17
e18
e19
e20
e21
e22
e23
e24
e25
e26
e27
e28

Variable counts (Group number 1)

Number of variables in your model: 57
Number of observed variables: 26
Number of unobserved variables: 31
Number of exogenous variables: 29
Number of endogenous variables: 28

Parameter Summary (Group number 1)

Weights Covariances Variances Means Intercepts Total
Fixed 31 0 0 0 0 31
Labeled 0 0 0 0 0 0
Unlabeled 26 0 29 0 0 55
Total 57 0 29 0 0 86

Assessment of normality (Group number 1)

Variable min max skew c.r. kurtosis c.r.
CG15 1.000 5.000 -.005 -.042 -1.017 -4.269
CG14 1.000 5.000 -.003 -.029 -.858 -3.601
CG13 1.000 5.000 -.067 -.566 -.929 -3.899
CG12 1.000 5.000 .045 .378 -.941 -3.950
CG11 1.000 5.000 -.027 -.226 -.917 -3.851
CG10 1.000 5.000 .077 .650 -.888 -3.730
CG9 1.000 5.000 -.003 -.025 -.921 -3.867
CG8 1.000 5.000 -.060 -.502 -1.008 -4.234
CG7 1.000 5.000 -.062 -.521 -.963 -4.043
CG6 1.000 5.000 -.033 -.274 -.915 -3.842
CG5 1.000 5.000 .017 .142 -.994 -4.175
CG4 1.000 5.000 .055 .465 -1.014 -4.257
CG3 1.000 5.000 .024 .198 -.939 -3.944
CG2 1.000 5.000 .086 .718 -.977 -4.101
CG1 1.000 5.000 -.007 -.058 -.905 -3.799
KS5 1.000 5.000 -.044 -.371 -.914 -3.839
KS4 1.000 5.000 -.041 -.346 -.940 -3.948
KS3 1.000 5.000 -.012 -.099 -.945 -3.968
KS2 1.000 5.000 .036 .300 -.968 -4.062
KS1 1.000 5.000 -.046 -.387 -1.062 -4.459
LPS6 1.000 5.000 -.025 -.208 -.831 -3.489
LPS5 1.000 5.000 -.032 -.270 -.940 -3.948
LPS4 1.000 5.000 .023 .194 -.771 -3.238
LPS3 1.000 5.000 .085 .714 -.800 -3.357
LPS2 1.000 5.000 .030 .254 -.820 -3.444
LPS1 1.000 5.000 .014 .115 -.843 -3.539
Multivariate -1.508 -.406

Observations farthest from the centroid (Mahalanobis distance) (Group number 1)

Observation number Mahalanobis d-squared p1 p2
374 46.180 .009 .975
389 46.151 .009 .886
143 44.666 .013 .908
169 43.323 .018 .944
137 43.308 .018 .876
403 43.262 .018 .779
315 41.054 .031 .975
198 40.289 .037 .987
14 40.150 .038 .979
375 39.931 .040 .973
194 39.847 .040 .956
210 39.486 .044 .960
225 39.426 .044 .937
423 39.360 .045 .908
145 39.039 .048 .917
286 38.856 .050 .906
85 38.838 .051 .862
337 38.794 .051 .815
369 38.348 .056 .869
63 37.990 .061 .899
13 37.975 .061 .859
38 37.706 .064 .876
206 37.498 .067 .880
341 37.358 .069 .870
321 37.343 .070 .827
43 37.220 .071 .812
273 37.211 .072 .757
420 36.878 .077 .815
141 36.751 .079 .805
192 36.696 .080 .770
59 36.576 .082 .758
71 36.567 .082 .701
396 36.555 .082 .641
151 36.212 .088 .730
365 36.185 .088 .682
181 36.116 .090 .650
66 36.075 .090 .605
279 35.893 .094 .630
202 35.732 .097 .647
223 35.723 .097 .588
418 35.692 .097 .539
406 35.679 .098 .481
48 35.678 .098 .417
323 35.446 .102 .478
232 35.209 .107 .545
326 35.199 .107 .488
344 35.060 .110 .503
154 34.960 .113 .498
57 34.933 .113 .452
12 34.650 .119 .553
186 34.630 .120 .505
351 34.536 .122 .500
417 34.171 .131 .652
92 34.069 .133 .655
405 33.943 .136 .671
287 33.917 .137 .633
5 33.762 .141 .667
233 33.581 .146 .715
162 33.562 .146 .677
350 33.520 .148 .650
313 33.511 .148 .603
168 33.467 .149 .576
72 33.367 .152 .584
117 33.299 .154 .572
128 33.273 .154 .535
242 33.192 .157 .533
239 33.143 .158 .511
385 33.094 .159 .490
179 32.848 .167 .595
52 32.719 .170 .626
97 32.614 .174 .642
258 32.533 .176 .644
334 32.425 .179 .663
7 32.386 .181 .639
32 32.294 .184 .650
93 32.269 .184 .618
378 32.191 .187 .620
55 32.131 .189 .611
329 32.119 .189 .571
363 32.103 .190 .532
176 31.943 .195 .592
261 31.902 .196 .572
398 31.722 .202 .645
422 31.696 .203 .616
73 31.669 .204 .587
386 31.662 .205 .544
371 31.647 .205 .507
412 31.632 .206 .469
44 31.613 .206 .435
58 31.601 .207 .396
149 31.536 .209 .395
253 31.396 .214 .447
413 31.367 .215 .421
240 31.355 .215 .383
81 31.310 .217 .369
291 31.305 .217 .330
404 31.282 .218 .303
68 31.017 .228 .440
381 30.983 .229 .419
65 30.935 .231 .409

Sample Moments (Group number 1)

Sample Covariances (Group number 1)

CG15 CG14 CG13 CG12 CG11 CG10 CG9 CG8 CG7 CG6 CG5 CG4 CG3 CG2 CG1 KS5 KS4 KS3 KS2 KS1 LPS6 LPS5 LPS4 LPS3 LPS2 LPS1
CG15 1.608
CG14 .766 1.468
CG13 .816 .830 1.480
CG12 .716 .690 .827 1.498
CG11 .891 .835 .847 .837 1.541
CG10 .719 .726 .780 .763 .870 1.493
CG9 .872 .780 .818 .740 .891 .893 1.532
CG8 .733 .719 .738 .636 .709 .594 .705 1.534
CG7 .801 .792 .806 .709 .761 .747 .764 .742 1.572
CG6 .809 .705 .742 .650 .801 .735 .783 .676 .678 1.551
CG5 .856 .837 .809 .712 .893 .785 .835 .723 .816 .768 1.612
CG4 .801 .705 .731 .740 .846 .790 .804 .645 .712 .759 .764 1.579
CG3 .823 .728 .792 .801 .771 .771 .749 .700 .783 .757 .742 .638 1.551
CG2 .759 .752 .735 .723 .769 .815 .770 .684 .799 .738 .823 .728 .735 1.521
CG1 .816 .785 .835 .688 .808 .686 .797 .730 .768 .697 .797 .716 .650 .743 1.482
KS5 .563 .541 .488 .457 .600 .516 .537 .401 .480 .446 .555 .520 .492 .408 .491 1.481
KS4 .438 .506 .499 .516 .472 .462 .528 .420 .399 .449 .491 .414 .416 .403 .470 .765 1.497
KS3 .473 .454 .452 .396 .536 .453 .502 .331 .418 .378 .522 .331 .421 .353 .456 .724 .767 1.530
KS2 .456 .513 .494 .435 .537 .485 .515 .407 .428 .447 .527 .362 .388 .407 .494 .799 .842 .714 1.579
KS1 .475 .470 .525 .463 .565 .487 .534 .383 .376 .419 .492 .385 .428 .435 .499 .757 .814 .747 .837 1.629
LPS6 .409 .440 .364 .385 .435 .357 .364 .449 .338 .312 .404 .331 .338 .352 .367 .476 .469 .421 .463 .432 1.385
LPS5 .515 .466 .489 .404 .457 .408 .402 .360 .409 .343 .506 .319 .362 .410 .504 .434 .431 .379 .534 .430 .673 1.439
LPS4 .489 .433 .439 .363 .497 .373 .376 .350 .435 .367 .393 .414 .343 .366 .412 .490 .367 .405 .468 .442 .699 .746 1.335
LPS3 .418 .433 .376 .380 .428 .330 .354 .397 .352 .319 .442 .296 .291 .347 .407 .384 .410 .396 .392 .383 .706 .706 .652 1.387
LPS2 .466 .449 .394 .434 .426 .377 .368 .374 .343 .341 .374 .428 .260 .330 .369 .427 .410 .399 .444 .345 .694 .758 .727 .651 1.398
LPS1 .269 .416 .236 .250 .430 .243 .312 .251 .329 .310 .385 .265 .220 .300 .338 .355 .371 .400 .475 .362 .702 .711 .650 .671 .685 1.402
Condition number = 35.129
Eigenvalues
15.631 3.788 2.448 1.124 1.035 .990 .961 .942 .908 .889 .836 .791 .784 .761 .709 .696 .687 .667 .647 .619 .588 .568 .550 .526 .496 .445
Determinant of sample covariance matrix = .093

Sample Correlations (Group number 1)

CG15 CG14 CG13 CG12 CG11 CG10 CG9 CG8 CG7 CG6 CG5 CG4 CG3 CG2 CG1 KS5 KS4 KS3 KS2 KS1 LPS6 LPS5 LPS4 LPS3 LPS2 LPS1
CG15 1.000
CG14 .499 1.000
CG13 .529 .563 1.000
CG12 .461 .465 .555 1.000
CG11 .566 .555 .561 .551 1.000
CG10 .464 .490 .525 .510 .574 1.000
CG9 .556 .520 .543 .488 .580 .591 1.000
CG8 .467 .479 .490 .420 .461 .392 .460 1.000
CG7 .504 .521 .529 .462 .489 .488 .492 .478 1.000
CG6 .512 .467 .490 .427 .518 .483 .508 .438 .435 1.000
CG5 .532 .544 .524 .458 .567 .506 .531 .460 .512 .486 1.000
CG4 .503 .463 .478 .481 .542 .514 .517 .415 .452 .485 .479 1.000
CG3 .521 .483 .523 .526 .499 .506 .486 .454 .501 .488 .469 .408 1.000
CG2 .485 .503 .490 .479 .502 .540 .505 .447 .517 .480 .526 .470 .479 1.000
CG1 .528 .532 .564 .462 .535 .461 .529 .484 .503 .460 .515 .468 .429 .495 1.000
KS5 .365 .367 .329 .307 .397 .347 .357 .266 .314 .295 .359 .340 .325 .272 .332 1.000
KS4 .282 .341 .335 .345 .311 .309 .348 .277 .260 .295 .316 .269 .273 .267 .315 .513 1.000
KS3 .302 .303 .300 .261 .349 .299 .328 .216 .270 .245 .332 .213 .273 .232 .303 .481 .507 1.000
KS2 .286 .337 .323 .283 .344 .316 .331 .261 .272 .286 .330 .229 .248 .262 .323 .522 .547 .459 1.000
KS1 .294 .304 .338 .296 .357 .312 .338 .242 .235 .263 .304 .240 .269 .276 .321 .487 .521 .473 .522 1.000
LPS6 .274 .308 .254 .267 .298 .248 .250 .308 .229 .213 .271 .224 .231 .242 .256 .332 .325 .289 .313 .288 1.000
LPS5 .339 .320 .335 .275 .307 .278 .270 .242 .272 .230 .332 .212 .242 .277 .345 .297 .294 .256 .354 .281 .477 1.000
LPS4 .334 .309 .313 .257 .346 .264 .263 .245 .300 .255 .268 .285 .238 .257 .293 .349 .260 .283 .322 .300 .514 .538 1.000
LPS3 .280 .303 .262 .264 .293 .229 .243 .272 .239 .218 .296 .200 .198 .239 .284 .268 .284 .272 .265 .255 .510 .500 .479 1.000
LPS2 .311 .313 .274 .300 .290 .261 .252 .255 .231 .231 .249 .288 .176 .226 .257 .297 .284 .272 .299 .228 .499 .534 .532 .468 1.000
LPS1 .180 .290 .164 .173 .293 .168 .213 .171 .221 .210 .256 .178 .149 .205 .235 .246 .256 .273 .319 .239 .504 .501 .475 .481 .490 1.000
Condition number = 34.767
Eigenvalues
10.325 2.601 1.631 .740 .689 .652 .642 .625 .591 .585 .555 .529 .516 .503 .478 .467 .458 .441 .430 .416 .392 .381 .363 .360 .335 .297

Models

Default model (Default model)

Notes for Model (Default model)

Computation of degrees of freedom (Default model)

Number of distinct sample moments: 351
Number of distinct parameters to be estimated: 55
Degrees of freedom (351 - 55): 296

Result (Default model)

Minimum was achieved
Chi-square = 291.096
Degrees of freedom = 296
Probability level = .570

Group number 1 (Group number 1 - Default model)

Estimates (Group number 1 - Default model)

Scalar Estimates (Group number 1 - Default model)

Maximum Likelihood Estimates

Regression Weights: (Group number 1 - Default model)

Estimate S.E. C.R. P Label
F2KS <--- F1LPS .634 .073 8.707 *** par_24
F3CG <--- F2KS .439 .065 6.790 *** par_25
F3CG <--- F1LPS .279 .066 4.256 *** par_26
LPS1 <--- F1LPS 1.000
LPS2 <--- F1LPS 1.048 .082 12.807 *** par_1
LPS3 <--- F1LPS .999 .081 12.371 *** par_2
LPS4 <--- F1LPS 1.042 .081 12.912 *** par_3
LPS5 <--- F1LPS 1.085 .083 13.027 *** par_4
LPS6 <--- F1LPS 1.035 .081 12.787 *** par_5
KS1 <--- F2KS 1.000
KS2 <--- F2KS 1.026 .078 13.225 *** par_6
KS3 <--- F2KS .924 .076 12.195 *** par_7
KS4 <--- F2KS 1.010 .076 13.316 *** par_8
KS5 <--- F2KS .976 .076 12.895 *** par_9
CG1 <--- F3CG 1.000
CG2 <--- F3CG .994 .072 13.794 *** par_10
CG3 <--- F3CG .982 .073 13.434 *** par_11
CG4 <--- F3CG .980 .073 13.340 *** par_12
CG5 <--- F3CG 1.066 .074 14.363 *** par_13
CG6 <--- F3CG .971 .073 13.326 *** par_14
CG7 <--- F3CG 1.007 .073 13.758 *** par_15
CG8 <--- F3CG .914 .072 12.673 *** par_16
CG9 <--- F3CG 1.068 .072 14.761 *** par_17
CG10 <--- F3CG 1.014 .072 14.139 *** par_18
CG11 <--- F3CG 1.105 .073 15.208 *** par_19
CG12 <--- F3CG .970 .072 13.534 *** par_20
CG13 <--- F3CG 1.055 .071 14.883 *** par_21
CG14 <--- F3CG 1.015 .071 14.359 *** par_22
CG15 <--- F3CG 1.064 .074 14.374 *** par_23

Standardized Regression Weights: (Group number 1 - Default model)

Estimate
F2KS <--- F1LPS .572
F3CG <--- F2KS .455
F3CG <--- F1LPS .261
LPS1 <--- F1LPS .681
LPS2 <--- F1LPS .714
LPS3 <--- F1LPS .683
LPS4 <--- F1LPS .727
LPS5 <--- F1LPS .729
LPS6 <--- F1LPS .709
KS1 <--- F2KS .700
KS2 <--- F2KS .729
KS3 <--- F2KS .667
KS4 <--- F2KS .737
KS5 <--- F2KS .716
CG1 <--- F3CG .708
CG2 <--- F3CG .695
CG3 <--- F3CG .679
CG4 <--- F3CG .672
CG5 <--- F3CG .723
CG6 <--- F3CG .672
CG7 <--- F3CG .692
CG8 <--- F3CG .636
CG9 <--- F3CG .744
CG10 <--- F3CG .715
CG11 <--- F3CG .767
CG12 <--- F3CG .683
CG13 <--- F3CG .748
CG14 <--- F3CG .722
CG15 <--- F3CG .723

Variances: (Group number 1 - Default model)

Estimate S.E. C.R. P Label
F1LPS .649 .087 7.485 *** par_27
e27 .536 .074 7.198 *** par_28
e28 .438 .056 7.849 *** par_29
e1 .753 .060 12.581 *** par_30
e2 .685 .056 12.186 *** par_31
e3 .740 .059 12.552 *** par_32
e4 .630 .052 12.003 *** par_33
e5 .675 .056 11.958 *** par_34
e6 .689 .056 12.225 *** par_35
e7 .832 .069 12.111 *** par_36
e8 .739 .063 11.652 *** par_37
e9 .849 .068 12.503 *** par_38
e10 .685 .059 11.524 *** par_39
e11 .722 .061 11.850 *** par_40
e12 .739 .054 13.589 *** par_41
e13 .787 .058 13.657 *** par_42
e14 .835 .061 13.723 *** par_43
e15 .866 .063 13.759 *** par_44
e16 .769 .057 13.508 *** par_45
e17 .851 .062 13.762 *** par_46
e18 .819 .060 13.668 *** par_47
e19 .913 .066 13.892 *** par_48
e20 .684 .051 13.372 *** par_49
e21 .729 .054 13.540 *** par_50
e22 .634 .048 13.191 *** par_51
e23 .800 .058 13.709 *** par_52
e24 .653 .049 13.345 *** par_53
e25 .703 .052 13.512 *** par_54
e26 .767 .057 13.505 *** par_55

Squared Multiple Correlations: (Group number 1 - Default model)

Estimate
F2KS .328
F3CG .411
CG15 .523
CG14 .521
CG13 .559
CG12 .466
CG11 .589
CG10 .512
CG9 .553
CG8 .405
CG7 .479
CG6 .451
CG5 .523
CG4 .452
CG3 .462
CG2 .483
CG1 .501
KS5 .513
KS4 .542
KS3 .445
KS2 .532
KS1 .489
LPS6 .502
LPS5 .531
LPS4 .528
LPS3 .467
LPS2 .510
LPS1 .463

Matrices (Group number 1 - Default model)

Implied (for all variables) Covariances (Group number 1 - Default model)

F1LPS F2KS F3CG CG15 CG14 CG13 CG12 CG11 CG10 CG9 CG8 CG7 CG6 CG5 CG4 CG3 CG2 CG1 KS5 KS4 KS3 KS2 KS1 LPS6 LPS5 LPS4 LPS3 LPS2 LPS1
F1LPS .649
F2KS .412 .797
F3CG .362 .465 .743
CG15 .385 .495 .790 1.608
CG14 .367 .472 .754 .802 1.468
CG13 .382 .491 .784 .834 .796 1.480
CG12 .351 .451 .720 .766 .731 .760 1.498
CG11 .400 .514 .821 .873 .833 .866 .796 1.541
CG10 .367 .472 .753 .801 .765 .795 .731 .833 1.493
CG9 .387 .497 .793 .844 .805 .837 .769 .877 .805 1.532
CG8 .331 .425 .679 .723 .689 .717 .659 .751 .689 .726 1.534
CG7 .365 .468 .748 .796 .759 .789 .725 .827 .759 .799 .684 1.572
CG6 .351 .451 .721 .767 .732 .761 .699 .797 .731 .770 .659 .726 1.551
CG5 .386 .495 .792 .842 .803 .835 .768 .875 .803 .845 .724 .797 .768 1.612
CG4 .355 .456 .728 .774 .739 .768 .706 .805 .738 .778 .666 .733 .707 .776 1.579
CG3 .355 .456 .729 .776 .740 .769 .707 .806 .739 .779 .667 .734 .708 .777 .715 1.551
CG2 .360 .462 .738 .786 .750 .779 .716 .816 .749 .789 .675 .744 .717 .787 .724 .725 1.521
CG1 .362 .465 .743 .790 .754 .784 .720 .821 .753 .793 .679 .748 .721 .792 .728 .729 .738 1.482
KS5 .402 .778 .454 .483 .461 .479 .440 .502 .460 .485 .415 .457 .441 .484 .445 .445 .451 .454 1.481
KS4 .416 .805 .469 .499 .476 .495 .455 .519 .476 .501 .429 .473 .456 .500 .460 .461 .467 .469 .785 1.497
KS3 .381 .737 .430 .457 .436 .454 .417 .475 .436 .459 .393 .433 .417 .458 .421 .422 .427 .430 .719 .744 1.530
KS2 .423 .818 .477 .508 .484 .504 .463 .527 .484 .510 .436 .481 .463 .509 .468 .468 .474 .477 .799 .826 .756 1.579
KS1 .412 .797 .465 .495 .472 .491 .451 .514 .472 .497 .425 .468 .451 .495 .456 .456 .462 .465 .778 .805 .737 .818 1.629
LPS6 .672 .426 .375 .399 .380 .396 .364 .414 .380 .400 .343 .377 .364 .399 .367 .368 .373 .375 .416 .430 .394 .437 .426 1.385
LPS5 .704 .447 .393 .418 .399 .414 .381 .434 .398 .420 .359 .396 .381 .419 .385 .386 .390 .393 .436 .451 .413 .458 .447 .729 1.439
LPS4 .677 .429 .377 .401 .383 .398 .366 .417 .383 .403 .345 .380 .366 .402 .370 .370 .375 .377 .419 .433 .397 .440 .429 .700 .734 1.335
LPS3 .648 .411 .362 .385 .367 .381 .351 .400 .367 .386 .331 .364 .351 .385 .354 .355 .359 .362 .401 .415 .380 .422 .411 .671 .703 .676 1.387
LPS2 .680 .431 .379 .404 .385 .400 .368 .419 .385 .405 .347 .382 .368 .404 .372 .372 .377 .379 .421 .436 .399 .443 .431 .704 .738 .709 .679 1.398
LPS1 .649 .412 .362 .385 .367 .382 .351 .400 .367 .387 .331 .365 .351 .386 .355 .355 .360 .362 .402 .416 .381 .423 .412 .672 .704 .677 .648 .680 1.402

Implied (for all variables) Correlations (Group number 1 - Default model)

F1LPS F2KS F3CG CG15 CG14 CG13 CG12 CG11 CG10 CG9 CG8 CG7 CG6 CG5 CG4 CG3 CG2 CG1 KS5 KS4 KS3 KS2 KS1 LPS6 LPS5 LPS4 LPS3 LPS2 LPS1
F1LPS 1.000
F2KS .572 1.000
F3CG .521 .604 1.000
CG15 .377 .437 .723 1.000
CG14 .376 .436 .722 .522 1.000
CG13 .390 .452 .748 .541 .540 1.000
CG12 .356 .413 .683 .494 .493 .511 1.000
CG11 .400 .464 .767 .555 .554 .574 .524 1.000
CG10 .373 .432 .715 .517 .516 .535 .488 .549 1.000
CG9 .388 .449 .744 .538 .537 .556 .508 .571 .532 1.000
CG8 .332 .385 .636 .460 .459 .476 .435 .488 .455 .473 1.000
CG7 .361 .418 .692 .501 .500 .517 .473 .531 .495 .515 .440 1.000
CG6 .350 .406 .672 .486 .485 .502 .459 .516 .481 .500 .427 .465 1.000
CG5 .377 .437 .723 .523 .522 .541 .494 .555 .517 .538 .460 .501 .486 1.000
CG4 .350 .406 .672 .486 .485 .503 .459 .516 .481 .500 .428 .465 .452 .486 1.000
CG3 .354 .411 .679 .491 .490 .508 .464 .521 .486 .505 .432 .470 .456 .491 .457 1.000
CG2 .362 .420 .695 .502 .502 .519 .474 .533 .497 .517 .442 .481 .467 .502 .467 .472 1.000
CG1 .369 .428 .708 .512 .511 .529 .483 .543 .506 .527 .450 .490 .476 .512 .476 .481 .492 1.000
KS5 .410 .716 .433 .313 .312 .324 .295 .332 .309 .322 .275 .299 .291 .313 .291 .294 .301 .306 1.000
KS4 .421 .737 .445 .322 .321 .333 .304 .342 .318 .331 .283 .308 .299 .322 .299 .302 .309 .315 .527 1.000
KS3 .382 .667 .403 .291 .291 .301 .275 .309 .288 .300 .256 .279 .271 .292 .271 .274 .280 .285 .478 .491 1.000
KS2 .417 .729 .441 .319 .318 .329 .301 .338 .315 .328 .280 .305 .296 .319 .296 .299 .306 .312 .522 .537 .486 1.000
KS1 .400 .700 .423 .306 .305 .316 .289 .324 .302 .314 .269 .293 .284 .306 .284 .287 .294 .299 .501 .515 .467 .510 1.000
LPS6 .709 .406 .370 .267 .267 .276 .252 .284 .264 .275 .235 .256 .248 .267 .248 .251 .257 .262 .290 .299 .271 .296 .284 1.000
LPS5 .729 .417 .380 .275 .274 .284 .259 .292 .272 .283 .242 .263 .255 .275 .255 .258 .264 .269 .299 .307 .278 .304 .292 .517 1.000
LPS4 .727 .416 .379 .274 .274 .283 .259 .291 .271 .282 .241 .262 .255 .274 .255 .257 .263 .268 .298 .306 .277 .303 .291 .515 .530 1.000
LPS3 .683 .391 .356 .258 .257 .266 .243 .273 .255 .265 .227 .247 .239 .258 .239 .242 .247 .252 .280 .288 .261 .285 .274 .484 .498 .496 1.000
LPS2 .714 .409 .372 .269 .269 .278 .254 .286 .266 .277 .237 .258 .250 .269 .250 .253 .259 .264 .293 .301 .273 .298 .286 .506 .520 .519 .488 1.000
LPS1 .681 .389 .355 .257 .256 .265 .242 .272 .254 .264 .226 .246 .238 .257 .238 .241 .246 .251 .279 .287 .260 .284 .272 .482 .496 .495 .465 .486 1.000

Implied Covariances (Group number 1 - Default model)

CG15 CG14 CG13 CG12 CG11 CG10 CG9 CG8 CG7 CG6 CG5 CG4 CG3 CG2 CG1 KS5 KS4 KS3 KS2 KS1 LPS6 LPS5 LPS4 LPS3 LPS2 LPS1
CG15 1.608
CG14 .802 1.468
CG13 .834 .796 1.480
CG12 .766 .731 .760 1.498
CG11 .873 .833 .866 .796 1.541
CG10 .801 .765 .795 .731 .833 1.493
CG9 .844 .805 .837 .769 .877 .805 1.532
CG8 .723 .689 .717 .659 .751 .689 .726 1.534
CG7 .796 .759 .789 .725 .827 .759 .799 .684 1.572
CG6 .767 .732 .761 .699 .797 .731 .770 .659 .726 1.551
CG5 .842 .803 .835 .768 .875 .803 .845 .724 .797 .768 1.612
CG4 .774 .739 .768 .706 .805 .738 .778 .666 .733 .707 .776 1.579
CG3 .776 .740 .769 .707 .806 .739 .779 .667 .734 .708 .777 .715 1.551
CG2 .786 .750 .779 .716 .816 .749 .789 .675 .744 .717 .787 .724 .725 1.521
CG1 .790 .754 .784 .720 .821 .753 .793 .679 .748 .721 .792 .728 .729 .738 1.482
KS5 .483 .461 .479 .440 .502 .460 .485 .415 .457 .441 .484 .445 .445 .451 .454 1.481
KS4 .499 .476 .495 .455 .519 .476 .501 .429 .473 .456 .500 .460 .461 .467 .469 .785 1.497
KS3 .457 .436 .454 .417 .475 .436 .459 .393 .433 .417 .458 .421 .422 .427 .430 .719 .744 1.530
KS2 .508 .484 .504 .463 .527 .484 .510 .436 .481 .463 .509 .468 .468 .474 .477 .799 .826 .756 1.579
KS1 .495 .472 .491 .451 .514 .472 .497 .425 .468 .451 .495 .456 .456 .462 .465 .778 .805 .737 .818 1.629
LPS6 .399 .380 .396 .364 .414 .380 .400 .343 .377 .364 .399 .367 .368 .373 .375 .416 .430 .394 .437 .426 1.385
LPS5 .418 .399 .414 .381 .434 .398 .420 .359 .396 .381 .419 .385 .386 .390 .393 .436 .451 .413 .458 .447 .729 1.439
LPS4 .401 .383 .398 .366 .417 .383 .403 .345 .380 .366 .402 .370 .370 .375 .377 .419 .433 .397 .440 .429 .700 .734 1.335
LPS3 .385 .367 .381 .351 .400 .367 .386 .331 .364 .351 .385 .354 .355 .359 .362 .401 .415 .380 .422 .411 .671 .703 .676 1.387
LPS2 .404 .385 .400 .368 .419 .385 .405 .347 .382 .368 .404 .372 .372 .377 .379 .421 .436 .399 .443 .431 .704 .738 .709 .679 1.398
LPS1 .385 .367 .382 .351 .400 .367 .387 .331 .365 .351 .386 .355 .355 .360 .362 .402 .416 .381 .423 .412 .672 .704 .677 .648 .680 1.402

Implied Correlations (Group number 1 - Default model)

CG15 CG14 CG13 CG12 CG11 CG10 CG9 CG8 CG7 CG6 CG5 CG4 CG3 CG2 CG1 KS5 KS4 KS3 KS2 KS1 LPS6 LPS5 LPS4 LPS3 LPS2 LPS1
CG15 1.000
CG14 .522 1.000
CG13 .541 .540 1.000
CG12 .494 .493 .511 1.000
CG11 .555 .554 .574 .524 1.000
CG10 .517 .516 .535 .488 .549 1.000
CG9 .538 .537 .556 .508 .571 .532 1.000
CG8 .460 .459 .476 .435 .488 .455 .473 1.000
CG7 .501 .500 .517 .473 .531 .495 .515 .440 1.000
CG6 .486 .485 .502 .459 .516 .481 .500 .427 .465 1.000
CG5 .523 .522 .541 .494 .555 .517 .538 .460 .501 .486 1.000
CG4 .486 .485 .503 .459 .516 .481 .500 .428 .465 .452 .486 1.000
CG3 .491 .490 .508 .464 .521 .486 .505 .432 .470 .456 .491 .457 1.000
CG2 .502 .502 .519 .474 .533 .497 .517 .442 .481 .467 .502 .467 .472 1.000
CG1 .512 .511 .529 .483 .543 .506 .527 .450 .490 .476 .512 .476 .481 .492 1.000
KS5 .313 .312 .324 .295 .332 .309 .322 .275 .299 .291 .313 .291 .294 .301 .306 1.000
KS4 .322 .321 .333 .304 .342 .318 .331 .283 .308 .299 .322 .299 .302 .309 .315 .527 1.000
KS3 .291 .291 .301 .275 .309 .288 .300 .256 .279 .271 .292 .271 .274 .280 .285 .478 .491 1.000
KS2 .319 .318 .329 .301 .338 .315 .328 .280 .305 .296 .319 .296 .299 .306 .312 .522 .537 .486 1.000
KS1 .306 .305 .316 .289 .324 .302 .314 .269 .293 .284 .306 .284 .287 .294 .299 .501 .515 .467 .510 1.000
LPS6 .267 .267 .276 .252 .284 .264 .275 .235 .256 .248 .267 .248 .251 .257 .262 .290 .299 .271 .296 .284 1.000
LPS5 .275 .274 .284 .259 .292 .272 .283 .242 .263 .255 .275 .255 .258 .264 .269 .299 .307 .278 .304 .292 .517 1.000
LPS4 .274 .274 .283 .259 .291 .271 .282 .241 .262 .255 .274 .255 .257 .263 .268 .298 .306 .277 .303 .291 .515 .530 1.000
LPS3 .258 .257 .266 .243 .273 .255 .265 .227 .247 .239 .258 .239 .242 .247 .252 .280 .288 .261 .285 .274 .484 .498 .496 1.000
LPS2 .269 .269 .278 .254 .286 .266 .277 .237 .258 .250 .269 .250 .253 .259 .264 .293 .301 .273 .298 .286 .506 .520 .519 .488 1.000
LPS1 .257 .256 .265 .242 .272 .254 .264 .226 .246 .238 .257 .238 .241 .246 .251 .279 .287 .260 .284 .272 .482 .496 .495 .465 .486 1.000

Residual Covariances (Group number 1 - Default model)

CG15 CG14 CG13 CG12 CG11 CG10 CG9 CG8 CG7 CG6 CG5 CG4 CG3 CG2 CG1 KS5 KS4 KS3 KS2 KS1 LPS6 LPS5 LPS4 LPS3 LPS2 LPS1
CG15 .000
CG14 -.036 .000
CG13 -.018 .034 .000
CG12 -.050 -.041 .067 .000
CG11 .018 .001 -.020 .041 .000
CG10 -.083 -.039 -.015 .032 .038 .000
CG9 .028 -.025 -.019 -.030 .015 .089 .000
CG8 .010 .029 .021 -.023 -.042 -.095 -.021 .000
CG7 .006 .033 .017 -.016 -.066 -.011 -.035 .058 .000
CG6 .042 -.027 -.018 -.049 .004 .004 .013 .017 -.048 .000
CG5 .014 .034 -.027 -.056 .019 -.018 -.011 -.001 .019 .000 .000
CG4 .027 -.034 -.038 .034 .042 .051 .026 -.020 -.021 .052 -.012 .000
CG3 .047 -.012 .022 .094 -.035 .031 -.029 .033 .048 .049 -.035 -.076 .000
CG2 -.027 .002 -.044 .006 -.047 .066 -.019 .008 .056 .021 .036 .005 .010 .000
CG1 .025 .031 .051 -.032 -.013 -.067 .003 .051 .020 -.024 .005 -.012 -.079 .004 .000
KS5 .080 .081 .009 .017 .098 .056 .052 -.014 .023 .006 .072 .075 .046 -.043 .037 .000
KS4 -.062 .030 .004 .061 -.047 -.014 .026 -.009 -.073 -.007 -.009 -.047 -.044 -.063 .001 -.021 .000
KS3 .016 .018 -.001 -.021 .061 .017 .043 -.063 -.014 -.039 .064 -.090 -.001 -.074 .026 .005 .023 .000
KS2 -.051 .029 -.010 -.028 .009 .001 .006 -.030 -.053 -.016 .019 -.106 -.081 -.068 .017 .001 .016 -.042 .000
KS1 -.019 -.001 .034 .012 .051 .015 .038 -.042 -.092 -.033 -.004 -.070 -.029 -.028 .034 -.021 .009 .011 .019 .000
LPS6 .010 .059 -.032 .021 .021 -.024 -.036 .107 -.039 -.052 .005 -.036 -.030 -.021 -.008 .060 .038 .027 .026 .006 .000
LPS5 .097 .067 .075 .023 .022 .010 -.018 .000 .014 -.038 .088 -.066 -.024 .020 .111 -.002 -.020 -.034 .076 -.017 -.056 .000
LPS4 .088 .050 .041 -.002 .080 -.010 -.027 .005 .055 .000 -.009 .044 -.028 -.009 .034 .072 -.066 .009 .028 .013 -.001 .012 .000
LPS3 .034 .066 -.006 .029 .029 -.036 -.032 .067 -.012 -.032 .057 -.059 -.064 -.013 .045 -.017 -.005 .016 -.030 -.028 .035 .003 -.024 .000
LPS2 .062 .064 -.006 .066 .007 -.008 -.037 .027 -.039 -.027 -.030 .056 -.113 -.047 -.010 .006 -.025 .000 .002 -.087 -.010 .020 .018 -.028 .000
LPS1 -.116 .049 -.146 -.101 .030 -.124 -.075 -.080 -.036 -.042 .000 -.090 -.136 -.060 -.024 -.047 -.044 .019 .053 -.050 .030 .007 -.027 .023 .005 .000

Standardized Residual Covariances (Group number 1 - Default model)

CG15 CG14 CG13 CG12 CG11 CG10 CG9 CG8 CG7 CG6 CG5 CG4 CG3 CG2 CG1 KS5 KS4 KS3 KS2 KS1 LPS6 LPS5 LPS4 LPS3 LPS2 LPS1
CG15 .000
CG14 -.428 .000
CG13 -.215 .419 .000
CG12 -.595 -.509 .822 .000
CG11 .205 .015 -.234 .491 .000
CG10 -.975 -.480 -.185 .399 .448 .000
CG9 .326 -.304 -.232 -.361 .169 1.063 .000
CG8 .123 .364 .258 -.280 -.501 -1.176 -.252 .000
CG7 .067 .397 .202 -.195 -.763 -.137 -.415 .706 .000
CG6 .486 -.335 -.223 -.600 .051 .052 .149 .204 -.568 .000
CG5 .156 .397 -.311 -.662 .212 -.207 -.124 -.006 .214 -.001 .000
CG4 .313 -.418 -.452 .413 .487 .620 .310 -.248 -.254 .624 -.141 .000
CG3 .549 -.146 .272 1.151 -.414 .377 -.350 .404 .575 .588 -.403 -.911 .000
CG2 -.315 .027 -.541 .079 -.561 .803 -.221 .102 .665 .256 .424 .054 .123 .000
CG1 .301 .383 .623 -.400 -.152 -.831 .042 .634 .245 -.291 .059 -.143 -.965 .052 .000
KS5 1.017 1.075 .113 .224 1.269 .740 .680 -.178 .294 .077 .909 .969 .603 -.569 .496 .000
KS4 -.779 .390 .053 .801 -.595 -.183 .340 -.116 -.937 -.088 -.111 -.595 -.574 -.825 .008 -.253 .000
KS3 .198 .234 -.019 -.277 .780 .218 .548 -.812 -.184 -.506 .805 -1.154 -.012 -.957 .341 .065 .281 .000
KS2 -.632 .368 -.121 -.356 .114 .008 .071 -.379 -.657 -.207 .229 -1.323 -1.015 -.859 .216 .006 .185 -.503 .000
KS1 -.237 -.019 .429 .154 .633 .191 .465 -.528 -1.137 -.408 -.044 -.866 -.355 -.346 .431 -.249 .106 .127 .215 .000
LPS6 .135 .825 -.438 .297 .283 -.325 -.496 1.462 -.530 -.703 .066 -.490 -.407 -.286 -.114 .821 .524 .372 .345 .082 .000
LPS5 1.269 .913 1.009 .307 .298 .134 -.240 .006 .179 -.510 1.139 -.867 -.319 .269 1.508 -.033 -.263 -.449 .989 -.215 -.723 .000
LPS4 1.189 .703 .580 -.034 1.098 -.138 -.379 .073 .757 .006 -.126 .604 -.382 -.132 .485 1.002 -.912 .120 .376 .171 -.015 .161 .000
LPS3 .450 .915 -.083 .407 .389 -.503 -.434 .919 -.158 -.430 .760 -.792 -.874 -.175 .631 -.240 -.069 .215 -.394 -.375 .470 .036 -.322 .000
LPS2 .820 .886 -.084 .910 .091 -.104 -.500 .369 -.525 -.372 -.402 .754 -1.522 -.647 -.140 .079 -.341 -.003 .022 -1.135 -.131 .253 .242 -.370 .000
LPS1 -1.533 .674 -2.009 -1.387 .407 -1.705 -1.013 -1.098 -.483 -.565 -.005 -1.209 -1.836 -.818 -.330 -.645 -.602 .261 .699 -.657 .396 .090 -.359 .306 .065 .000

Factor Score Weights (Group number 1 - Default model)

CG15 CG14 CG13 CG12 CG11 CG10 CG9 CG8 CG7 CG6 CG5 CG4 CG3 CG2 CG1 KS5 KS4 KS3 KS2 KS1 LPS6 LPS5 LPS4 LPS3 LPS2 LPS1
F1LPS .004 .004 .005 .003 .005 .004 .004 .003 .003 .003 .004 .003 .003 .004 .004 .012 .014 .010 .013 .011 .129 .138 .142 .116 .131 .114
F2KS .007 .008 .009 .007 .009 .007 .008 .005 .007 .006 .007 .006 .006 .007 .007 .157 .171 .126 .161 .139 .014 .015 .015 .012 .014 .012
F3CG .061 .064 .072 .054 .077 .062 .069 .044 .054 .051 .061 .050 .052 .056 .060 .007 .008 .006 .007 .006 .004 .005 .005 .004 .004 .004

Total Effects (Group number 1 - Default model)

F1LPS F2KS F3CG
F2KS .634 .000 .000
F3CG .558 .439 .000
CG15 .593 .467 1.064
CG14 .566 .446 1.015
CG13 .588 .463 1.055
CG12 .541 .426 .970
CG11 .616 .485 1.105
CG10 .565 .445 1.014
CG9 .596 .469 1.068
CG8 .510 .402 .914
CG7 .561 .442 1.007
CG6 .541 .426 .971
CG5 .594 .468 1.066
CG4 .547 .430 .980
CG3 .547 .431 .982
CG2 .554 .437 .994
CG1 .558 .439 1.000
KS5 .619 .976 .000
KS4 .640 1.010 .000
KS3 .586 .924 .000
KS2 .651 1.026 .000
KS1 .634 1.000 .000
LPS6 1.035 .000 .000
LPS5 1.085 .000 .000
LPS4 1.042 .000 .000
LPS3 .999 .000 .000
LPS2 1.048 .000 .000
LPS1 1.000 .000 .000

Standardized Total Effects (Group number 1 - Default model)

F1LPS F2KS F3CG
F2KS .572 .000 .000
F3CG .521 .455 .000
CG15 .377 .329 .723
CG14 .376 .328 .722
CG13 .390 .340 .748
CG12 .356 .311 .683
CG11 .400 .349 .767
CG10 .373 .325 .715
CG9 .388 .338 .744
CG8 .332 .289 .636
CG7 .361 .315 .692
CG6 .350 .306 .672
CG5 .377 .329 .723
CG4 .350 .306 .672
CG3 .354 .309 .679
CG2 .362 .316 .695
CG1 .369 .322 .708
KS5 .410 .716 .000
KS4 .421 .737 .000
KS3 .382 .667 .000
KS2 .417 .729 .000
KS1 .400 .700 .000
LPS6 .709 .000 .000
LPS5 .729 .000 .000
LPS4 .727 .000 .000
LPS3 .683 .000 .000
LPS2 .714 .000 .000
LPS1 .681 .000 .000

Direct Effects (Group number 1 - Default model)

F1LPS F2KS F3CG
F2KS .634 .000 .000
F3CG .279 .439 .000
CG15 .000 .000 1.064
CG14 .000 .000 1.015
CG13 .000 .000 1.055
CG12 .000 .000 .970
CG11 .000 .000 1.105
CG10 .000 .000 1.014
CG9 .000 .000 1.068
CG8 .000 .000 .914
CG7 .000 .000 1.007
CG6 .000 .000 .971
CG5 .000 .000 1.066
CG4 .000 .000 .980
CG3 .000 .000 .982
CG2 .000 .000 .994
CG1 .000 .000 1.000
KS5 .000 .976 .000
KS4 .000 1.010 .000
KS3 .000 .924 .000
KS2 .000 1.026 .000
KS1 .000 1.000 .000
LPS6 1.035 .000 .000
LPS5 1.085 .000 .000
LPS4 1.042 .000 .000
LPS3 .999 .000 .000
LPS2 1.048 .000 .000
LPS1 1.000 .000 .000

Standardized Direct Effects (Group number 1 - Default model)

F1LPS F2KS F3CG
F2KS .572 .000 .000
F3CG .261 .455 .000
CG15 .000 .000 .723
CG14 .000 .000 .722
CG13 .000 .000 .748
CG12 .000 .000 .683
CG11 .000 .000 .767
CG10 .000 .000 .715
CG9 .000 .000 .744
CG8 .000 .000 .636
CG7 .000 .000 .692
CG6 .000 .000 .672
CG5 .000 .000 .723
CG4 .000 .000 .672
CG3 .000 .000 .679
CG2 .000 .000 .695
CG1 .000 .000 .708
KS5 .000 .716 .000
KS4 .000 .737 .000
KS3 .000 .667 .000
KS2 .000 .729 .000
KS1 .000 .700 .000
LPS6 .709 .000 .000
LPS5 .729 .000 .000
LPS4 .727 .000 .000
LPS3 .683 .000 .000
LPS2 .714 .000 .000
LPS1 .681 .000 .000

Indirect Effects (Group number 1 - Default model)

F1LPS F2KS F3CG
F2KS .000 .000 .000
F3CG .278 .000 .000
CG15 .593 .467 .000
CG14 .566 .446 .000
CG13 .588 .463 .000
CG12 .541 .426 .000
CG11 .616 .485 .000
CG10 .565 .445 .000
CG9 .596 .469 .000
CG8 .510 .402 .000
CG7 .561 .442 .000
CG6 .541 .426 .000
CG5 .594 .468 .000
CG4 .547 .430 .000
CG3 .547 .431 .000
CG2 .554 .437 .000
CG1 .558 .439 .000
KS5 .619 .000 .000
KS4 .640 .000 .000
KS3 .586 .000 .000
KS2 .651 .000 .000
KS1 .634 .000 .000
LPS6 .000 .000 .000
LPS5 .000 .000 .000
LPS4 .000 .000 .000
LPS3 .000 .000 .000
LPS2 .000 .000 .000
LPS1 .000 .000 .000

Standardized Indirect Effects (Group number 1 - Default model)

F1LPS F2KS F3CG
F2KS .000 .000 .000
F3CG .260 .000 .000
CG15 .377 .329 .000
CG14 .376 .328 .000
CG13 .390 .340 .000
CG12 .356 .311 .000
CG11 .400 .349 .000
CG10 .373 .325 .000
CG9 .388 .338 .000
CG8 .332 .289 .000
CG7 .361 .315 .000
CG6 .350 .306 .000
CG5 .377 .329 .000
CG4 .350 .306 .000
CG3 .354 .309 .000
CG2 .362 .316 .000
CG1 .369 .322 .000
KS5 .410 .000 .000
KS4 .421 .000 .000
KS3 .382 .000 .000
KS2 .417 .000 .000
KS1 .400 .000 .000
LPS6 .000 .000 .000
LPS5 .000 .000 .000
LPS4 .000 .000 .000
LPS3 .000 .000 .000
LPS2 .000 .000 .000
LPS1 .000 .000 .000

Modification Indices (Group number 1 - Default model)

Covariances: (Group number 1 - Default model)

M.I. Par Change
e23 <--> e24 4.111 .076
e21 <--> e26 5.880 -.094
e20 <--> e21 7.606 .102
e19 <--> e21 6.363 -.106
e18 <--> e22 4.014 -.075
e14 <--> e23 6.212 .104
e12 <--> e21 4.023 -.076
e12 <--> e14 4.767 -.088
e11 <--> e15 4.503 .091
e10 <--> e23 4.416 .085
e10 <--> e22 4.122 -.075
e6 <--> e19 7.070 .113
e5 <--> e15 4.274 -.086
e5 <--> e12 4.100 .078
e4 <--> e10 4.660 -.082
e2 <--> e15 5.488 .097
e1 <--> e26 6.075 -.100
e1 <--> e24 7.113 -.101
e1 <--> e22 4.492 .079

Variances: (Group number 1 - Default model)

M.I. Par Change

Regression Weights: (Group number 1 - Default model)

M.I. Par Change
CG14 <--- LPS1 4.967 .079
CG11 <--- LPS1 4.272 .071
CG8 <--- LPS6 4.139 .082
CG3 <--- LPS2 4.605 -.083
KS5 <--- CG4 5.315 .082
LPS1 <--- CG15 7.844 -.099
LPS1 <--- CG13 8.392 -.107
LPS1 <--- CG12 4.874 -.081
LPS1 <--- CG10 4.438 -.077

Minimization History (Default model)

Iteration Negative
eigenvalues		 Condition # Smallest
eigenvalue		 Diameter F NTries Ratio
0 e 6 -1.564 9999.000 5013.420 0 9999.000
1 e 6 -.108 3.904 2200.531 19 .175
2 e 1 -.103 2.381 711.344 5 .676
3 e 0 35.679 1.097 373.907 5 .913
4 e 0 37.772 .651 316.649 2 .000
5 e 0 57.992 .396 292.662 1 1.115
6 e 0 69.803 .152 291.119 1 1.072
7 e 0 69.386 .021 291.096 1 1.013
8 e 0 69.685 .000 291.096 1 1.000

Pairwise Parameter Comparisons (Default model)

Variance-covariance Matrix of Estimates (Default model)

par_1 par_2 par_3 par_4 par_5 par_6 par_7 par_8 par_9 par_10 par_11 par_12 par_13 par_14 par_15 par_16 par_17 par_18 par_19 par_20 par_21 par_22 par_23 par_24 par_25 par_26 par_27 par_28 par_29 par_30 par_31 par_32 par_33 par_34 par_35 par_36 par_37 par_38 par_39 par_40 par_41 par_42 par_43 par_44 par_45 par_46 par_47 par_48 par_49 par_50 par_51 par_52 par_53 par_54 par_55
par_1 .007
par_2 .003 .007
par_3 .004 .003 .007
par_4 .004 .004 .004 .007
par_5 .004 .003 .004 .004 .007
par_6 .000 .000 .000 .000 .000 .006
par_7 .000 .000 .000 .000 .000 .003 .006
par_8 .000 .000 .000 .000 .000 .003 .003 .006
par_9 .000 .000 .000 .000 .000 .003 .003 .003 .006
par_10 .000 .000 .000 .000 .000 .000 .000 .000 .000 .005
par_11 .000 .000 .000 .000 .000 .000 .000 .000 .000 .002 .005
par_12 .000 .000 .000 .000 .000 .000 .000 .000 .000 .002 .002 .005
par_13 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .003 .006
par_14 .000 .000 .000 .000 .000 .000 .000 .000 .000 .002 .002 .002 .003 .005
par_15 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .002 .003 .002 .005
par_16 .000 .000 .000 .000 .000 .000 .000 .000 .000 .002 .002 .002 .002 .002 .002 .005
par_17 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .003 .003 .003 .003 .002 .005
par_18 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .003 .003 .003 .003 .002 .003 .005
par_19 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .003 .003 .003 .003 .003 .003 .003 .005
par_20 .000 .000 .000 .000 .000 .000 .000 .000 .000 .002 .002 .002 .003 .002 .002 .002 .003 .003 .003 .005
par_21 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .003 .003 .003 .003 .002 .003 .003 .003 .003 .005
par_22 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .003 .003 .002 .003 .002 .003 .003 .003 .002 .003 .005
par_23 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .003 .003 .003 .003 .002 .003 .003 .003 .003 .003 .003 .005
par_24 .002 .002 .002 .002 .002 -.002 -.002 -.002 -.002 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .005
par_25 .000 .000 .000 .000 .000 .001 .001 .001 .001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 .004
par_26 .001 .001 .001 .001 .001 .000 .000 .000 .000 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 -.001 .000 -.002 .004
par_27 -.005 -.004 -.005 -.005 -.004 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.003 .000 -.001 .008
par_28 .000 .000 .000 .000 .000 -.003 -.003 -.003 -.003 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 -.002 .000 .000 .006
par_29 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.002 -.002 -.002 -.002 -.002 -.002 -.002 -.002 -.002 -.002 -.002 -.002 -.002 -.002 .000 .001 .001 .000 .000 .003
par_30 .001 .001 .001 .001 .001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .000 .000 .004
par_31 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_32 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_33 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_34 .000 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_35 .000 .000 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_36 .000 .000 .000 .000 .000 .001 .001 .001 .001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .005
par_37 .000 .000 .000 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004
par_38 .000 .000 .000 .000 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .005
par_39 .000 .000 .000 .000 .000 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004
par_40 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004
par_41 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_42 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_43 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004
par_44 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004
par_45 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_46 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004
par_47 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004
par_48 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004
par_49 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_50 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_51 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .002
par_52 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_53 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .002
par_54 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003
par_55 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003

Correlations of Estimates (Default model)

par_1 par_2 par_3 par_4 par_5 par_6 par_7 par_8 par_9 par_10 par_11 par_12 par_13 par_14 par_15 par_16 par_17 par_18 par_19 par_20 par_21 par_22 par_23 par_24 par_25 par_26 par_27 par_28 par_29 par_30 par_31 par_32 par_33 par_34 par_35 par_36 par_37 par_38 par_39 par_40 par_41 par_42 par_43 par_44 par_45 par_46 par_47 par_48 par_49 par_50 par_51 par_52 par_53 par_54 par_55
par_1 1.000
par_2 .515 1.000
par_3 .558 .526 1.000
par_4 .556 .529 .566 1.000
par_5 .534 .522 .547 .534 1.000
par_6 .000 -.002 -.002 .000 -.001 1.000
par_7 .000 .000 -.001 -.002 -.001 .484 1.000
par_8 .001 .000 -.002 .000 .001 .543 .504 1.000
par_9 .002 .000 .001 .000 .001 .529 .491 .529 1.000
par_10 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_11 .000 .000 .000 .000 .000 .000 .000 .000 .001 .474 1.000
par_12 .001 .000 .000 -.001 .000 .000 .000 .000 .001 .467 .455 1.000
par_13 .000 .000 .000 .000 .000 .000 .001 .000 .001 .503 .491 .485 1.000
par_14 .000 .000 .000 -.001 .000 .000 .000 .001 .000 .468 .461 .455 .485 1.000
par_15 .000 .000 .000 .000 .000 .001 .001 .000 .001 .482 .473 .463 .500 .462 1.000
par_16 .000 .000 .000 .000 .001 .000 .000 .001 .000 .440 .434 .425 .458 .427 .441 1.000
par_17 .000 .000 .000 -.001 .000 .000 .000 .000 .000 .514 .505 .501 .536 .500 .511 .469 1.000
par_18 .000 .000 .000 .000 .000 .000 .000 .000 .000 .501 .490 .485 .517 .482 .494 .449 .537 1.000
par_19 .000 .000 .000 -.001 .000 .000 .000 -.001 .000 .529 .521 .518 .554 .516 .525 .483 .570 .552 1.000
par_20 .001 .000 .000 .000 .000 .000 .000 .001 .000 .475 .471 .461 .491 .457 .471 .432 .506 .492 .526 1.000
par_21 .001 .000 .001 .000 .000 .000 .000 .000 .000 .514 .509 .498 .536 .499 .515 .473 .552 .533 .569 .513 1.000
par_22 .000 .000 .000 -.001 .000 .000 .000 .001 .001 .499 .490 .482 .522 .482 .499 .458 .533 .514 .551 .490 .538 1.000
par_23 .001 .000 .001 .000 .001 .000 .000 .000 .001 .499 .494 .486 .522 .487 .498 .458 .537 .513 .554 .490 .536 .517 1.000
par_24 .369 .355 .383 .380 .374 -.344 -.321 -.359 -.341 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_25 -.008 -.010 -.013 -.014 -.008 .271 .259 .274 .292 -.241 -.232 -.232 -.246 -.230 -.239 -.220 -.250 -.243 -.261 -.233 -.254 -.246 -.249 -.181 1.000
par_26 .198 .191 .207 .208 .190 -.003 -.006 .004 -.016 -.149 -.152 -.145 -.156 -.148 -.148 -.134 -.166 -.159 -.165 -.148 -.162 -.152 -.153 .097 -.475 1.000
par_27 -.636 -.609 -.649 -.647 -.629 .001 .001 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 -.436 .015 -.232 1.000
par_28 .000 .000 -.003 -.002 -.007 -.596 -.546 -.592 -.590 .000 .000 .000 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .242 -.322 .053 .006 1.000
par_29 -.005 -.005 -.006 -.006 -.003 .005 -.001 .003 -.008 -.543 -.534 -.527 -.570 -.528 -.542 -.498 -.585 -.564 -.606 -.539 -.586 -.570 -.568 -.001 .186 .167 .006 .004 1.000
par_30 .159 .146 .172 .162 .149 -.002 -.001 .000 .001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .000 .001 .113 -.021 .083 -.172 -.009 -.009 1.000
par_31 -.163 .012 -.005 -.005 .007 -.001 -.002 -.002 -.002 .000 .000 -.001 .000 .000 .000 .000 .000 -.001 .000 -.001 .000 .000 -.001 .008 -.008 .002 .016 -.011 .000 -.023 1.000
par_32 .019 -.146 .019 .010 -.004 .002 .000 -.001 .001 .000 .000 .001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .008 -.004 .002 .004 -.009 .000 -.006 -.045 1.000
par_33 -.019 -.001 -.181 -.016 -.010 .001 .001 .004 -.001 .000 .000 -.001 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 -.001 -.015 .001 -.013 .033 -.005 .002 -.048 -.018 -.046 1.000
par_34 -.006 .002 -.002 -.170 .027 -.002 .002 .000 .001 .001 .001 .001 .000 .001 .001 .001 .001 .001 .001 .001 .000 .001 .000 -.001 .002 -.013 .017 -.008 .002 -.025 -.017 -.028 -.026 1.000
par_35 .018 -.002 .015 .036 -.153 .001 .000 -.001 -.001 .000 -.001 .000 .000 .000 .000 -.001 .000 .000 .000 -.001 .000 .000 .000 -.004 -.008 .016 .003 .003 -.005 -.004 -.039 .000 -.035 -.080 1.000
par_36 .001 -.001 -.001 -.001 .000 .186 .172 .191 .197 .000 .000 .001 .001 .000 .001 .000 .000 .000 .000 .000 .000 .001 .000 -.093 .110 -.024 .000 -.207 -.007 -.001 -.003 .001 .002 .001 .000 1.000
par_37 .002 .003 .002 .000 .003 -.193 .025 .004 .010 .000 .001 .001 .000 .000 .000 .000 .000 .000 .000 .001 .000 .000 .001 .013 .027 -.022 -.002 .014 -.019 .003 -.001 -.003 -.001 .004 -.003 -.025 1.000
par_38 .000 .000 .001 .002 .001 .020 -.168 -.003 .002 .000 .000 .001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .016 .006 -.011 -.001 .006 -.005 .001 .001 .001 .000 -.003 .000 -.020 -.063 1.000
par_39 -.001 -.002 .002 .000 -.001 .000 -.008 -.200 .018 .000 .000 .000 .000 -.001 .000 -.001 .000 .000 .001 -.001 .000 .000 .001 .039 .027 -.036 .000 -.001 -.015 .000 .002 .003 -.006 .000 .002 -.033 -.037 -.016 1.000
par_40 -.002 -.001 -.004 -.001 -.002 -.008 -.013 .004 -.203 .000 -.001 -.002 -.001 .000 -.001 .000 .000 -.001 -.001 .000 .000 -.001 -.001 .022 -.027 .005 .002 .031 .007 -.003 .001 -.002 .004 -.002 .001 -.054 -.046 -.025 -.071 1.000
par_41 .000 .000 .000 -.001 .000 .000 .000 .000 .001 .065 .072 .064 .067 .066 .063 .054 .070 .075 .074 .068 .065 .064 .065 .000 -.031 -.022 .000 .000 -.070 .000 -.001 .000 .000 .001 -.001 .001 .000 .000 .000 -.001 1.000
par_42 .000 .000 .000 .000 .000 .000 .001 .000 .001 -.065 -.001 .000 -.003 -.002 -.005 -.001 .002 -.006 .005 .000 .005 .000 .003 .000 .008 .000 .000 -.001 -.005 .000 .000 .000 .000 .000 .000 .001 .001 -.001 .001 -.001 -.004 1.000
par_43 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.008 -.070 .000 -.004 -.011 -.012 -.010 -.005 -.010 -.004 -.016 -.010 -.006 -.012 .000 .004 .011 .000 .000 .004 .000 -.001 .000 .000 .000 .001 .000 -.001 .000 .000 .001 -.018 -.001 1.000
par_44 -.001 .000 .000 .001 .000 .000 .000 -.001 -.001 -.002 .005 -.063 .000 -.006 .001 .001 -.004 -.006 -.005 -.004 .002 .002 -.004 .000 .006 .001 .000 .000 -.002 .000 .001 -.001 .001 -.001 .000 -.001 -.001 -.001 .000 .002 -.006 -.002 -.014 1.000
par_45 .001 .000 .001 .000 .001 -.001 -.001 .000 -.001 -.003 .005 .002 -.067 .001 -.001 .001 .002 .003 -.001 .007 .004 -.003 -.001 .001 -.001 .000 -.001 .001 .004 .001 -.001 .001 -.001 .001 .000 -.001 .000 .001 -.001 .000 -.003 .003 -.011 -.006 1.000
par_46 .000 .000 .000 .001 .001 -.001 .000 -.001 .000 -.004 -.006 -.007 -.002 -.064 .002 -.003 -.004 -.003 -.003 .002 .000 .000 -.006 .000 .003 .005 -.001 .000 .001 .001 .000 .000 .000 -.001 .000 .000 .001 -.001 .001 -.001 -.008 .000 .004 .005 -.004 1.000
par_47 .000 .000 .000 .000 .000 -.001 -.001 -.001 -.001 -.003 -.003 .004 .000 .006 -.063 -.004 .006 .004 .009 .004 .000 -.001 .002 .001 .006 -.002 .000 .001 -.005 .000 -.001 .000 .001 .000 .000 -.001 .001 .000 .000 .000 .000 .007 .005 -.007 -.001 -.011 1.000
par_48 .000 -.001 .000 .000 -.001 .000 .000 -.001 .000 .004 .002 .006 .004 .003 -.001 -.055 .007 .012 .008 .006 .003 .002 .003 .000 .004 -.006 .000 .000 -.005 -.001 .000 .001 .000 -.001 .001 .000 .001 -.001 .001 -.001 .005 -.001 .002 -.005 -.003 .000 .006 1.000
par_49 .000 .000 .001 .001 .000 .000 .000 .000 .000 .002 .004 -.003 .002 -.002 .005 .003 -.071 -.011 -.002 .004 .003 .004 -.003 .000 -.007 .013 -.001 .000 .002 .001 .000 .000 -.001 .000 .000 .000 .000 .000 .000 .000 -.005 -.009 -.011 .002 -.009 -.001 -.013 -.008 1.000
par_50 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.015 -.011 -.013 -.006 -.008 -.006 .003 -.018 -.076 -.013 -.012 -.006 -.003 .001 .000 .001 .011 .000 .000 .009 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .000 -.020 .009 .002 .006 -.009 -.003 -.007 -.019 .017 1.000
par_51 .001 .001 .000 .001 .001 .001 .000 .002 .000 .005 .003 -.008 -.005 -.003 .007 .004 -.005 -.008 -.076 -.008 .001 -.002 -.004 .000 .001 -.001 -.001 -.001 .010 .001 .000 .000 .001 -.001 .000 .001 .000 .001 -.003 .001 -.010 -.018 -.014 .005 -.002 -.004 -.023 -.013 -.002 .005 1.000
par_52 -.001 -.001 .000 .000 -.001 .000 .001 -.001 .001 -.004 -.012 -.006 .002 .001 -.002 -.001 -.001 -.007 -.008 -.067 -.010 .001 .001 .000 .003 .002 .001 .000 .005 -.001 .001 .000 -.001 .000 .000 .000 -.001 -.001 .002 -.001 -.010 -.003 .012 .002 -.015 -.011 -.006 -.006 -.011 .003 .004 1.000
par_53 -.001 -.001 -.001 -.001 -.001 .001 .001 .000 .002 .012 .003 .011 .010 .009 .004 .003 .010 .009 .010 -.002 -.065 .002 .009 -.001 -.002 .001 .001 -.001 -.006 -.001 .000 .000 .001 .001 -.001 .001 .000 .000 .001 -.002 .008 -.016 .001 -.013 -.013 -.009 -.001 .001 -.013 -.011 -.015 .010 1.000
par_54 .000 .000 .001 .000 .000 -.001 .000 -.001 -.001 .004 .005 .008 .000 .007 .000 .000 .008 .009 .005 .008 .000 -.064 .008 .001 .001 -.008 .000 .001 .003 .001 .000 .000 -.001 .000 .000 -.001 .000 .000 .000 .000 .003 -.004 -.007 -.011 .003 -.009 .003 .002 -.013 -.015 -.007 -.012 .004 1.000
par_55 -.001 -.001 -.001 -.001 -.001 .000 .000 .001 -.001 .006 -.002 .000 .001 -.002 .002 .001 .000 .012 .001 .008 .005 .007 -.065 -.001 .005 -.007 .001 .000 -.001 -.002 .001 .000 .001 .001 -.001 .000 -.001 .001 -.001 .002 .001 -.010 .004 .001 -.002 .004 -.003 -.001 .001 -.024 -.002 -.014 -.011 -.013 1.000

Critical Ratios for Differences between Parameters (Default model)

par_1 par_2 par_3 par_4 par_5 par_6 par_7 par_8 par_9 par_10 par_11 par_12 par_13 par_14 par_15 par_16 par_17 par_18 par_19 par_20 par_21 par_22 par_23 par_24 par_25 par_26 par_27 par_28 par_29 par_30 par_31 par_32 par_33 par_34 par_35 par_36 par_37 par_38 par_39 par_40 par_41 par_42 par_43 par_44 par_45 par_46 par_47 par_48 par_49 par_50 par_51 par_52 par_53 par_54 par_55
par_1 .000
par_2 -.617 .000
par_3 -.077 .553 .000
par_4 .476 1.085 .561 .000
par_5 -.161 .465 -.088 -.626 .000
par_6 -.191 .249 -.139 -.514 -.079 .000
par_7 -1.108 -.670 -1.062 -1.424 -1.000 -1.309 .000
par_8 -.345 .099 -.294 -.670 -.233 -.230 1.127 .000
par_9 -.645 -.203 -.596 -.967 -.534 -.676 .677 -.454 .000
par_10 -.494 -.041 -.443 -.825 -.381 -.305 .666 -.148 .172 .000
par_11 -.605 -.156 -.556 -.933 -.493 -.421 .543 -.266 .052 -.168 .000
par_12 -.618 -.170 -.568 -.944 -.506 -.434 .527 -.279 .037 -.187 -.020 .000
par_13 .159 .611 .214 -.174 .275 .364 1.331 .528 .844 .979 1.130 1.140 .000
par_14 -.706 -.257 -.657 -1.033 -.594 -.524 .440 -.370 -.052 -.313 -.144 -.123 -1.272 .000
par_15 -.374 .076 -.323 -.704 -.261 -.183 .783 -.025 .292 .173 .337 .353 -.795 .478 .000
par_16 -1.224 -.778 -1.179 -1.548 -1.115 -1.057 -.096 -.909 -.590 -1.044 -.869 -.840 -1.982 -.725 -1.203 .000
par_17 .184 .641 .239 -.153 .301 .392 1.371 .558 .878 1.039 1.195 1.207 .036 1.341 .849 2.063 .000
par_18 -.311 .144 -.259 -.645 -.196 -.117 .860 .044 .364 .279 .445 .462 -.716 .591 .099 1.320 -.778 .000
par_19 .523 .982 .582 .183 .642 .741 1.722 .911 1.231 1.582 1.733 1.744 .573 1.879 1.384 2.591 .553 1.333 .000
par_20 -.719 -.267 -.670 -1.048 -.606 -.536 .435 -.381 -.061 -.330 -.158 -.136 -1.300 -.012 -.498 .723 -1.373 -.613 -1.928 .000
par_21 .067 .527 .122 -.272 .185 .274 1.260 .440 .762 .867 1.032 1.039 -.148 1.175 .681 1.917 -.189 .596 -.751 1.214 .000
par_22 -.305 .152 -.253 -.641 -.190 -.110 .873 .052 .375 .292 .460 .475 -.713 .606 .112 1.351 -.768 .012 -1.330 .628 -.592 .000
par_23 .143 .595 .198 -.190 .259 .348 1.315 .512 .828 .952 1.111 1.119 -.025 1.251 .771 1.961 -.061 .690 -.599 1.277 .122 .686 .000
par_24 -4.746 -4.170 -4.770 -5.161 -4.650 -3.181 -2.404 -3.064 -2.813 -3.514 -3.369 -3.344 -4.150 -3.268 -3.611 -2.735 -4.227 -3.718 -4.580 -3.286 -4.144 -3.752 -4.139 .000
par_25 -5.813 -5.383 -5.792 -6.084 -5.729 -6.788 -5.644 -6.700 -6.391 -5.147 -5.010 -4.982 -5.706 -4.923 -5.225 -4.442 -5.799 -5.343 -6.100 -4.952 -5.734 -5.385 -5.691 -1.842 .000
par_26 -8.161 -7.670 -8.214 -8.513 -8.043 -7.345 -6.418 -7.299 -6.904 -6.845 -6.668 -6.653 -7.390 -6.588 -6.914 -6.120 -7.484 -7.026 -7.822 -6.638 -7.455 -7.111 -7.394 -3.809 -1.431 .000
par_27 -2.615 -2.325 -2.583 -2.824 -2.551 -3.242 -2.390 -3.128 -2.838 -3.058 -2.930 -2.910 -3.647 -2.838 -3.151 -2.350 -3.708 -3.241 -4.030 -2.849 -3.623 -3.268 -3.634 .112 1.955 3.077 .000
par_28 -4.628 -4.212 -4.602 -4.909 -4.524 -3.611 -2.940 -3.532 -3.288 -4.421 -4.271 -4.245 -5.037 -4.173 -4.509 -3.649 -5.124 -4.624 -5.471 -4.198 -5.050 -4.664 -5.027 -1.082 .854 2.660 -.994 .000
par_29 -6.150 -5.705 -6.144 -6.440 -6.072 -6.177 -5.172 -6.086 -5.707 -4.944 -4.808 -4.791 -5.439 -4.730 -5.015 -4.295 -5.516 -5.103 -5.789 -4.751 -5.465 -5.144 -5.435 -2.142 -.021 2.013 -2.059 -1.060 .000
par_30 -3.163 -2.640 -3.152 -3.523 -3.033 -2.793 -1.779 -2.661 -2.318 -2.578 -2.425 -2.401 -3.283 -2.313 -2.690 -1.727 -3.360 -2.800 -3.746 -2.328 -3.263 -2.833 -3.271 1.333 3.520 5.569 .910 2.257 3.835 .000
par_31 -3.406 -3.206 -3.621 -3.970 -3.565 -3.560 -2.534 -3.434 -3.084 -3.381 -3.216 -3.187 -4.088 -3.103 -3.487 -2.507 -4.179 -3.610 -4.573 -3.125 -4.090 -3.652 -4.073 .557 2.857 4.704 .349 1.589 3.125 -.813 .000
par_32 -3.086 -2.428 -3.054 -3.400 -2.948 -2.946 -1.924 -2.810 -2.467 -2.734 -2.578 -2.554 -3.440 -2.466 -2.845 -1.876 -3.520 -2.957 -3.908 -2.481 -3.423 -2.992 -3.427 1.131 3.426 5.228 .863 2.135 3.722 -.154 .655 .000
par_33 -4.263 -3.826 -3.965 -4.588 -4.182 -4.234 -3.195 -4.124 -3.756 -4.084 -3.908 -3.876 -4.794 -3.794 -4.184 -3.188 -4.901 -4.322 -5.300 -3.826 -4.819 -4.373 -4.780 -.045 2.291 4.150 -.193 1.029 2.515 -1.505 -.710 -1.358 .000
par_34 -3.744 -3.290 -3.726 -3.789 -3.700 -3.662 -2.644 -3.543 -3.194 -3.489 -3.324 -3.298 -4.193 -3.213 -3.595 -2.617 -4.288 -3.719 -4.681 -3.236 -4.198 -3.762 -4.180 .442 2.747 4.543 .248 1.480 2.993 -.935 -.128 -.784 .574 .000
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Model Fit Summary

CMIN

Model NPAR CMIN DF P CMIN/DF
Default model 55 291.096 296 .570 .983
Saturated model 351 .000 0
Independence model 26 5461.091 325 .000 16.803

RMR, GFI

Model RMR GFI AGFI PGFI
Default model .043 .950 .941 .801
Saturated model .000 1.000
Independence model .559 .213 .150 .197

Baseline Comparisons

Model NFI
Delta1		 RFI
rho1		 IFI
Delta2		 TLI
rho2		 CFI
Default model .947 .941 1.001 1.001 1.000
Saturated model 1.000 1.000 1.000
Independence model .000 .000 .000 .000 .000

Parsimony-Adjusted Measures

Model PRATIO PNFI PCFI
Default model .911 .862 .911
Saturated model .000 .000 .000
Independence model 1.000 .000 .000

NCP

Model NCP LO 90 HI 90
Default model .000 .000 38.764
Saturated model .000 .000 .000
Independence model 5136.091 4899.845 5378.746

FMIN

Model FMIN F0 LO 90 HI 90
Default model .690 .000 .000 .092
Saturated model .000 .000 .000 .000
Independence model 12.941 12.171 11.611 12.746

RMSEA

Model RMSEA LO 90 HI 90 PCLOSE
Default model .000 .000 .018 1.000
Independence model .194 .189 .198 .000

AIC

Model AIC BCC BIC CAIC
Default model 401.096 408.615 623.701 678.701
Saturated model 702.000 749.985 2122.628 2473.628
Independence model 5513.091 5516.645 5618.323 5644.323

ECVI

Model ECVI LO 90 HI 90 MECVI
Default model .950 .962 1.054 .968
Saturated model 1.664 1.664 1.664 1.777
Independence model 13.064 12.504 13.639 13.073

HOELTER

Model HOELTER
.05		 HOELTER
.01
Default model 489 516
Independence model 29 30

Execution time summary

Minimization: .017
Miscellaneous: .355
Bootstrap: .000
Total: .372