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Analysis Summary

Date and Time

Date: 2024년 4월 27일 토요일
Time: 오후 9:31:58

Title

키오스크: 2024년 4월 27일 토요일 오후 9:31

Groups

Group number 1 (Group number 1)

Notes for Group (Group number 1)

The model is recursive.
Sample size = 227

Variable Summary (Group number 1)

Your model contains the following variables (Group number 1)

Observed, endogenous variables
X1_4
X1_3
X1_2
X1_1
X2_4
X2_3
X2_2
X2_1
X3_2
X3_1
X4_4
X4_3
X4_2
X4_1
X5_1
X5_2
X5_3
X5_4
X6_4
X6_3
X6_2
X6_1
X7_1
X7_2
X7_3
X7_4
Unobserved, endogenous variables
유용성2
용이성2
사용의도2
Unobserved, exogenous variables
혁신성2
e14
e13
e12
e11
낙관성2
e24
e23
e22
e21
정확성2
e32
e31
편의성2
e44
e43
e42
e41
e51
e52
e53
e54
e64
e63
e62
e61
e71
e72
e73
e74
d1
d2
d3

Variable counts (Group number 1)

Number of variables in your model: 62
Number of observed variables: 26
Number of unobserved variables: 36
Number of exogenous variables: 33
Number of endogenous variables: 29

Parameter Summary (Group number 1)

Weights Covariances Variances Means Intercepts Total
Fixed 36 0 0 33 3 72
Labeled 0 0 0 0 0 0
Unlabeled 29 0 33 0 26 88
Total 65 0 33 33 29 160

Models

Default model (Default model)

Notes for Model (Default model)

Computation of degrees of freedom (Default model)

Number of distinct sample moments: 377
Number of distinct parameters to be estimated: 88
Degrees of freedom (377 - 88): 289

Result (Default model)

Iteration limit reached
The results that follow are therefore incorrect.
Chi-square = 1369.791
Degrees of freedom = 289
Probability level = .000

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
유용성2 <--- 혁신성2 -.012 .036 -.329 .742 par_20
유용성2 <--- 낙관성2 .443 .055 8.079 *** par_21
유용성2 <--- 정확성2 .008 .046 .180 .857 par_22
용이성2 <--- 혁신성2 .068 .038 1.794 .073 par_23
용이성2 <--- 낙관성2 .188 .050 3.796 *** par_24
용이성2 <--- 정확성2 .000 .004 .020 .984 par_25
용이성2 <--- 편의성2 .252 .071 3.572 *** par_26
유용성2 <--- 편의성2 .835 .111 7.546 *** par_29
사용의도2 <--- 용이성2 .212 .086 2.464 .014 par_27
사용의도2 <--- 유용성2 .900 .091 9.888 *** par_28
X1_4 <--- 혁신성2 1.000
X1_3 <--- 혁신성2 .742 .077 9.591 *** par_1
X1_2 <--- 혁신성2 .763 .055 13.949 *** par_2
X1_1 <--- 혁신성2 .812 .054 15.080 *** par_3
X2_4 <--- 낙관성2 1.000
X2_3 <--- 낙관성2 1.060 .079 13.450 *** par_4
X2_2 <--- 낙관성2 .715 .073 9.815 *** par_5
X2_1 <--- 낙관성2 1.026 .079 13.005 *** par_6
X3_2 <--- 정확성2 1.000
X3_1 <--- 정확성2 .101 .514 .197 .844 par_7
X4_4 <--- 편의성2 1.000
X4_3 <--- 편의성2 1.062 .148 7.166 *** par_8
X4_2 <--- 편의성2 1.284 .152 8.449 *** par_9
X4_1 <--- 편의성2 1.018 .136 7.508 *** par_10
X5_1 <--- 유용성2 1.000
X5_2 <--- 유용성2 1.009 .090 11.197 *** par_11
X5_3 <--- 유용성2 1.041 .092 11.292 *** par_12
X5_4 <--- 유용성2 .989 .085 11.681 *** par_13
X6_4 <--- 용이성2 1.000
X6_3 <--- 용이성2 1.040 .120 8.639 *** par_14
X6_2 <--- 용이성2 1.338 .139 9.648 *** par_15
X6_1 <--- 용이성2 1.168 .129 9.072 *** par_16
X7_1 <--- 사용의도2 1.000
X7_2 <--- 사용의도2 1.063 .075 14.151 *** par_17
X7_3 <--- 사용의도2 .999 .069 14.409 *** par_18
X7_4 <--- 사용의도2 .990 .070 14.167 *** par_19

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

Estimate
유용성2 <--- 혁신성2 -.016
유용성2 <--- 낙관성2 .502
유용성2 <--- 정확성2 .028
용이성2 <--- 혁신성2 .130
용이성2 <--- 낙관성2 .293
용이성2 <--- 정확성2 .000
용이성2 <--- 편의성2 .297
유용성2 <--- 편의성2 .714
사용의도2 <--- 용이성2 .136
사용의도2 <--- 유용성2 .791
X1_4 <--- 혁신성2 .905
X1_3 <--- 혁신성2 .594
X1_2 <--- 혁신성2 .781
X1_1 <--- 혁신성2 .828
X2_4 <--- 낙관성2 .773
X2_3 <--- 낙관성2 .871
X2_2 <--- 낙관성2 .652
X2_1 <--- 낙관성2 .839
X3_2 <--- 정확성2 2.590
X3_1 <--- 정확성2 .301
X4_4 <--- 편의성2 .583
X4_3 <--- 편의성2 .618
X4_2 <--- 편의성2 .824
X4_1 <--- 편의성2 .662
X5_1 <--- 유용성2 .795
X5_2 <--- 유용성2 .714
X5_3 <--- 유용성2 .719
X5_4 <--- 유용성2 .739
X6_4 <--- 용이성2 .672
X6_3 <--- 용이성2 .687
X6_2 <--- 용이성2 .814
X6_1 <--- 용이성2 .732
X7_1 <--- 사용의도2 .752
X7_2 <--- 사용의도2 .890
X7_3 <--- 사용의도2 .904
X7_4 <--- 사용의도2 .890

Intercepts: (Group number 1 - Default model)

Estimate S.E. C.R. P Label
X1_4 3.511 .058 60.162 *** par_30
X1_3 2.811 .066 42.643 *** par_31
X1_2 3.921 .052 75.989 *** par_32
X1_1 3.652 .052 70.540 *** par_33
X2_4 3.837 .056 68.929 *** par_34
X2_3 3.850 .052 73.466 *** par_35
X2_2 4.247 .047 90.015 *** par_36
X2_1 3.802 .053 72.241 *** par_37
X3_2 3.524 .050 70.334 *** par_38
X3_1 3.652 .044 83.768 *** par_39
X4_4 3.220 .056 57.847 *** par_40
X4_3 3.740 .056 67.042 *** par_41
X4_2 4.053 .051 80.092 *** par_42
X4_1 4.018 .050 80.455 *** par_43
X5_1 3.815 .048 79.863 *** par_44
X5_2 3.722 .054 69.345 *** par_45
X5_3 3.749 .055 68.181 *** par_46
X5_4 3.885 .051 76.458 *** par_47
X6_4 3.952 .041 96.090 *** par_48
X6_3 4.009 .042 95.814 *** par_49
X6_2 3.868 .045 85.164 *** par_50
X6_1 3.846 .044 87.190 *** par_51
X7_1 3.652 .057 63.552 *** par_52
X7_2 3.784 .052 73.315 *** par_53
X7_3 3.709 .048 77.740 *** par_54
X7_4 3.674 .048 76.498 *** par_55

Variances: (Group number 1 - Default model)

Estimate S.E. C.R. P Label
혁신성2 .630 .076 8.296 *** par_56
낙관성2 .418 .063 6.619 *** par_57
정확성2 3.806 19.306 .197 .844 par_58
편의성2 .238 .054 4.433 *** par_59
d1 .077 .019 4.124 *** par_60
d2 .140 .027 5.131 *** par_61
d3 .118 .023 5.228 *** par_62
e14 .140 .029 4.755 *** par_63
e13 .635 .064 9.948 *** par_64
e12 .235 .028 8.523 *** par_65
e11 .190 .025 7.506 *** par_66
e24 .282 .033 8.644 *** par_67
e23 .150 .024 6.384 *** par_68
e22 .289 .030 9.663 *** par_69
e21 .186 .025 7.363 *** par_70
e32 -3.239 19.310 -.168 .867 par_71
e31 .391 .201 1.942 .052 par_72
e44 .462 .048 9.585 *** par_73
e43 .435 .046 9.371 *** par_74
e42 .186 .030 6.251 *** par_75
e41 .317 .035 9.027 *** par_76
e51 .190 .022 8.462 *** par_77
e52 .319 .034 9.331 *** par_78
e53 .330 .036 9.293 *** par_79
e54 .265 .029 9.119 *** par_80
e64 .210 .024 8.838 *** par_81
e63 .209 .024 8.677 *** par_82
e62 .157 .025 6.330 *** par_83
e61 .204 .025 8.069 *** par_84
e71 .325 .033 9.704 *** par_85
e72 .126 .016 7.848 *** par_86
e73 .094 .013 7.348 *** par_87
e74 .108 .014 7.821 *** par_88

Matrices (Group number 1 - Default model)

Implied Covariances (Group number 1 - Default model)

X7_4 X7_3 X7_2 X7_1 X6_1 X6_2 X6_3 X6_4 X5_4 X5_3 X5_2 X5_1 X4_1 X4_2 X4_3 X4_4 X3_1 X3_2 X2_1 X2_2 X2_3 X2_4 X1_1 X1_2 X1_3 X1_4
X7_4 .521
X7_3 .417 .515
X7_2 .444 .448 .602
X7_1 .418 .421 .448 .746
X6_1 .130 .131 .140 .132 .440
X6_2 .149 .151 .160 .151 .270 .466
X6_3 .116 .117 .125 .117 .210 .240 .396
X6_4 .112 .113 .120 .113 .202 .231 .179 .382
X5_4 .305 .307 .327 .308 .098 .112 .087 .084 .584
X5_3 .321 .323 .344 .324 .103 .118 .092 .088 .336 .683
X5_2 .311 .314 .334 .314 .100 .114 .089 .085 .325 .342 .651
X5_1 .308 .311 .331 .311 .099 .113 .088 .085 .322 .339 .329 .516
X4_1 .193 .195 .207 .195 .072 .082 .064 .061 .200 .211 .204 .202 .564
X4_2 .244 .246 .262 .246 .090 .103 .080 .077 .253 .266 .258 .255 .311 .579
X4_3 .202 .203 .216 .204 .075 .085 .066 .064 .209 .220 .213 .211 .257 .325 .703
X4_4 .190 .191 .204 .192 .070 .080 .063 .060 .197 .207 .201 .199 .242 .306 .253 .700
X3_1 .003 .003 .003 .003 .000 .000 .000 .000 .003 .003 .003 .003 .000 .000 .000 .000 .430
X3_2 .028 .029 .030 .029 .000 .000 .000 .000 .031 .033 .032 .032 .000 .000 .000 .000 .385 .567
X2_1 .186 .188 .200 .188 .094 .108 .084 .081 .188 .198 .192 .190 .000 .000 .000 .000 .000 .000 .626
X2_2 .130 .131 .140 .131 .066 .075 .059 .056 .131 .138 .134 .133 .000 .000 .000 .000 .000 .000 .307 .503
X2_3 .193 .194 .207 .195 .097 .112 .087 .083 .194 .205 .198 .197 .000 .000 .000 .000 .000 .000 .455 .317 .621
X2_4 .182 .183 .195 .184 .092 .105 .082 .079 .183 .193 .187 .185 .000 .000 .000 .000 .000 .000 .429 .299 .444 .700
X1_1 .002 .002 .002 .002 .041 .047 .036 .035 -.006 -.006 -.006 -.006 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .606
X1_2 .002 .002 .002 .002 .038 .044 .034 .033 -.006 -.006 -.006 -.006 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .390 .602
X1_3 .002 .002 .002 .002 .037 .043 .033 .032 -.005 -.006 -.006 -.006 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .379 .356 .982
X1_4 .002 .002 .003 .002 .050 .057 .045 .043 -.007 -.008 -.008 -.007 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .511 .480 .467 .770

Implied Correlations (Group number 1 - Default model)

X7_4 X7_3 X7_2 X7_1 X6_1 X6_2 X6_3 X6_4 X5_4 X5_3 X5_2 X5_1 X4_1 X4_2 X4_3 X4_4 X3_1 X3_2 X2_1 X2_2 X2_3 X2_4 X1_1 X1_2 X1_3 X1_4
X7_4 1.000
X7_3 .805 1.000
X7_2 .792 .804 1.000
X7_1 .669 .680 .669 1.000
X6_1 .272 .276 .272 .230 1.000
X6_2 .303 .307 .302 .256 .596 1.000
X6_3 .256 .259 .255 .216 .503 .559 1.000
X6_4 .250 .254 .250 .211 .492 .547 .461 1.000
X5_4 .553 .561 .552 .467 .193 .215 .181 .177 1.000
X5_3 .537 .546 .537 .454 .188 .209 .176 .172 .531 1.000
X5_2 .534 .542 .533 .450 .186 .207 .175 .171 .528 .513 1.000
X5_1 .594 .603 .594 .502 .208 .231 .195 .191 .588 .572 .568 1.000
X4_1 .356 .362 .356 .301 .144 .160 .135 .132 .349 .340 .337 .376 1.000
X4_2 .444 .451 .443 .375 .179 .199 .168 .164 .435 .423 .420 .468 .545 1.000
X4_3 .333 .338 .332 .281 .134 .149 .126 .123 .326 .317 .315 .351 .409 .509 1.000
X4_4 .314 .319 .314 .265 .127 .141 .119 .116 .308 .299 .297 .331 .386 .480 .360 1.000
X3_1 .006 .006 .006 .005 .000 .000 .000 .000 .006 .006 .006 .007 .000 .000 .000 .000 1.000
X3_2 .052 .053 .052 .044 .001 .001 .001 .001 .054 .053 .053 .059 .000 .000 .000 .000 .780 1.000
X2_1 .326 .331 .326 .275 .180 .200 .169 .165 .311 .303 .301 .335 .000 .000 .000 .000 .000 .000 1.000
X2_2 .254 .258 .254 .214 .140 .155 .131 .128 .242 .235 .234 .260 .000 .000 .000 .000 .000 .000 .547 1.000
X2_3 .339 .344 .338 .286 .187 .208 .175 .171 .323 .314 .312 .348 .000 .000 .000 .000 .000 .000 .730 .568 1.000
X2_4 .301 .305 .300 .254 .166 .184 .155 .152 .287 .279 .277 .309 .000 .000 .000 .000 .000 .000 .648 .504 .673 1.000
X1_1 .003 .003 .003 .003 .079 .088 .074 .072 -.010 -.010 -.010 -.011 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
X1_2 .003 .003 .003 .003 .074 .083 .070 .068 -.009 -.009 -.009 -.010 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .646 1.000
X1_3 .002 .003 .002 .002 .057 .063 .053 .052 -.007 -.007 -.007 -.008 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .492 .464 1.000
X1_4 .004 .004 .004 .003 .086 .096 .081 .079 -.011 -.011 -.011 -.012 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .749 .706 .537 1.000

Implied Means (Group number 1 - Default model)

X7_4 X7_3 X7_2 X7_1 X6_1 X6_2 X6_3 X6_4 X5_4 X5_3 X5_2 X5_1 X4_1 X4_2 X4_3 X4_4 X3_1 X3_2 X2_1 X2_2 X2_3 X2_4 X1_1 X1_2 X1_3 X1_4
3.674 3.709 3.784 3.652 3.846 3.868 4.009 3.952 3.885 3.749 3.722 3.815 4.018 4.053 3.740 3.220 3.652 3.524 3.802 4.247 3.850 3.837 3.652 3.921 2.811 3.511

Notes for Group/Model (Group number 1 - Default model)

The following variances are negative. (Group number 1 - Default model)

e32
-3.239
This solution is not admissible.

Minimization History (Default model)

Iteration Negative
eigenvalues		 Condition # Smallest
eigenvalue		 Diameter F NTries Ratio
0 e 14 -.776 9999.000 4799.403 0 9999.000
1 e 14 -.400 2.776 3194.719 19 .516
2 e 6 -.195 1.051 2443.494 5 .985
3 e* 4 -.205 .678 2165.877 4 .612
4 e* 1 -.026 .907 1715.175 5 .897
5 e 1 -.502 .686 1513.309 5 .786
6 e 0 5584.552 .534 1421.599 8 .892
7 e 0 5670.724 .909 1399.044 1 .506
8 e 0 5822.901 .414 1372.053 1 1.096
9 e 0 14680.189 .174 1370.739 1 1.095
10 e 0 6203.246 .290 1370.677 1 .324
11 e 0 364128.987 .097 1370.380 1 1.021
12 e 0 13833.578 .239 1370.308 5 .000
13 e 0 79008.688 .112 1370.200 1 1.186
14 e 0 17394.235 .251 1370.181 2 .000
15 e 0 229126.785 .091 1370.091 1 1.090
16 e 0 29513.136 .231 1370.069 3 .000
17 e 0 197148.984 .101 1370.020 1 1.172
18 e 0 78445.094 .141 1370.001 3 .000
19 e 0 66209.708 .198 1369.977 1 1.198
20 e 0 156924.715 .138 1369.954 1 1.344
21 e 0 50450.489 .277 1369.951 1 .160
22 e 0 907861.550 .080 1369.919 1 1.073
23 e 0 179406.410 .148 1369.909 4 .000
24 e 0 122895.101 .216 1369.898 1 1.071
25 e 0 406702.942 .123 1369.885 1 1.294
26 e 0 163484.853 .188 1369.879 2 .000
27 e 0 432060.242 .136 1369.869 1 1.338
28 e 0 257561.873 .157 1369.864 2 .000
29 e 0 333270.711 .173 1369.856 1 1.350
30 e 0 289342.514 .200 1369.850 1 1.245
31 e 0 598010.071 .154 1369.844 1 1.367
32 e 0 264433.668 .260 1369.841 1 .673
33 e 0 2188392.147 .099 1369.833 1 1.170
34 e 0 662014.217 .172 1369.830 3 .000
35 e 0 884172.500 .181 1369.826 1 1.349
36 e 0 835359.464 .205 1369.822 1 1.261
37 e 0 1508410.806 .165 1369.818 1 1.371
38 e 0 761144.272 .258 1369.816 1 .830
39 e 0 4574026.679 .111 1369.812 1 1.215
40 e 0 735709.998 .299 1369.812 2 .000
41 e 0 12333905.284 .084 1369.807 1 1.092
42 e 0 1022478.010 .299 1369.806 3 .000
43 e 0 14223274.511 .089 1369.802 1 1.107
44 e 0 1565730.364 .273 1369.801 3 .000
45 e 0 12528000.210 .106 1369.798 1 1.177
46 e 0 3741770.866 .188 1369.797 3 .000
47 e 0 4939356.538 .195 1369.795 1 1.356
48 e 0 4134420.972 .229 1369.794 1 1.233
49 e 0 8263121.501 .171 1369.792 1 1.370

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_56 par_57 par_58 par_59 par_60 par_61 par_62 par_63 par_64 par_65 par_66 par_67 par_68 par_69 par_70 par_71 par_72 par_73 par_74 par_75 par_76 par_77 par_78 par_79 par_80 par_81 par_82 par_83 par_84 par_85 par_86 par_87 par_88
par_1 .006
par_2 .001 .003
par_3 .001 .001 .003
par_4 .000 .000 .000 .006
par_5 .000 .000 .000 .003 .005
par_6 .000 .000 .000 .004 .003 .006
par_7 .000 .000 .000 .000 .000 .000 .264
par_8 .000 .000 .000 .000 .000 .000 .000 .022
par_9 .000 .000 .000 .000 .000 .000 .000 .014 .023
par_10 .000 .000 .000 .000 .000 .000 .000 .011 .014 .018
par_11 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .008
par_12 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .008
par_13 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .007
par_14 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .014
par_15 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .010 .019
par_16 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .008 .011 .017
par_17 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .006
par_18 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004 .005
par_19 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .004 .004 .005
par_20 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_21 .000 .000 .000 .002 .001 .002 .000 .000 .000 .000 -.001 -.001 -.001 .000 .000 .000 .000 .000 .000 .000 .003
par_22 .000 .000 .000 .000 .000 .000 .024 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .002
par_23 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 -.001 .000 .000 .000 .000 .000 .000 .001
par_24 .000 .000 .000 .001 .000 .001 .000 .000 .000 .000 .000 .000 .000 -.001 -.002 -.002 .000 .000 .000 .000 .000 .000 .000 .002
par_25 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000
par_26 .000 .000 .000 .000 .000 .000 .000 .003 .003 .003 .000 .000 .000 -.002 -.002 -.002 .000 .000 .000 .000 .000 .000 .000 .000 .000 .005
par_27 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .002 .002 .002 -.001 -.001 -.001 .000 .000 .000 .000 .000 .000 -.001 .007
par_28 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .003 .003 .000 .000 .000 -.004 -.003 -.003 .000 -.001 .000 .000 .000 .000 .000 -.001 .008
par_29 .000 .000 .000 .000 .000 .000 .000 .009 .011 .009 -.003 -.003 -.003 .000 .000 .000 .000 .000 .000 .000 .001 .000 .000 .000 .000 .002 .000 -.002 .012
par_30 .000 .000 .000 .000 .000 .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_31 .000 .000 .000 .000 .000 .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 .004
par_32 .000 .000 .000 .000 .000 .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 .002 .003
par_33 .000 .000 .000 .000 .000 .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 .002 .002 .003
par_34 .000 .000 .000 .000 .000 .000 .000 .000 .000 .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 .000 .000 .000 .000 .000 .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 .003
par_36 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .001 .002
par_37 .000 .000 .000 .000 .000 .000 .000 .000 .000 .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 .002 .001 .003
par_38 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .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_39 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .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 .002
par_40 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .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_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 .001 .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 .001 .001 .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 .001 .001 .001 .002
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 .001 .001 .001 .001 .000 .000 .001 .001 .001 .001 .002
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 .001 .001 .001 .001 .000 .000 .001 .001 .001 .001 .001 .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 .001 .001 .001 .001 .000 .000 .001 .001 .001 .001 .002 .002 .003
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 .001 .001 .001 .001 .000 .000 .001 .001 .001 .001 .001 .001 .001 .003
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 .002
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 .001 .002
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 .001 .001 .001 .000 .001 .001 .002
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 .001 .001 .001 .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 .001 .001 .001 .001 .000 .000 .001 .001 .001 .001 .001 .001 .001 .001 .000 .001 .001 .001 .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 .001 .001 .001 .001 .000 .000 .001 .001 .001 .001 .001 .001 .002 .001 .001 .001 .001 .001 .002 .003
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 .001 .001 .001 .001 .000 .000 .001 .001 .001 .001 .001 .001 .001 .001 .000 .001 .001 .001 .002 .002 .002
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 .001 .001 .001 .001 .000 .000 .001 .001 .001 .001 .001 .001 .001 .001 .000 .001 .001 .001 .002 .002 .002 .002
par_56 -.001 -.002 -.002 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .006
par_57 .000 .000 .000 -.003 -.002 -.003 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .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 .000 .000 .004
par_58 .000 .000 .000 .000 .000 .000 -9.924 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.890 .000 .000 -.008 .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 .000 372.707
par_59 .000 .000 .000 .000 .000 .000 .000 -.005 -.007 -.005 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .000 .000 -.004 .000 .000 .000 .000 .000 .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_60 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .031 .000 .000
par_61 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.002 -.003 -.002 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_62 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 -.001 -.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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_63 .001 .001 .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 .000 .000 .000 .000 .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 .001
par_64 -.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 .000 .000 .000 .000 .000 .000 .000 .000 .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_65 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_66 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_67 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_68 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_69 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_70 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_71 .000 .000 .000 .000 .000 .000 9.927 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .891 .000 .000 .008 .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 -372.797 .000 -.031 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 372.890
par_72 .000 .000 .000 .000 .000 .000 -.102 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.009 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 3.829 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -3.829 .040
par_73 .000 .000 .000 .000 .000 .000 .000 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .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_74 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .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_75 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_76 .000 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_77 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_78 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_79 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_80 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_81 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .001 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_82 .000 .000 .000 .000 .000 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_83 .000 .000 .000 .000 .000 .000 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_84 .000 .000 .000 .000 .000 .000 .000 .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 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_85 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001
par_86 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000
par_87 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000
par_88 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000

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_56 par_57 par_58 par_59 par_60 par_61 par_62 par_63 par_64 par_65 par_66 par_67 par_68 par_69 par_70 par_71 par_72 par_73 par_74 par_75 par_76 par_77 par_78 par_79 par_80 par_81 par_82 par_83 par_84 par_85 par_86 par_87 par_88
par_1 1.000
par_2 .234 1.000
par_3 .261 .391 1.000
par_4 .000 .000 .000 1.000
par_5 .000 .000 .000 .469 1.000
par_6 .000 .000 .000 .613 .452 1.000
par_7 .000 .000 .000 .000 .000 .000 1.000
par_8 .000 .000 .000 .000 .000 .000 .000 1.000
par_9 .000 .000 .000 .000 .000 .000 .000 .639 1.000
par_10 .000 .000 .000 .000 .000 .000 .000 .569 .669 1.000
par_11 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_12 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .388 1.000
par_13 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .401 .405 1.000
par_14 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_15 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .578 1.000
par_16 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .544 .603 1.000
par_17 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_18 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .748 1.000
par_19 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .736 .749 1.000
par_20 -.005 -.008 -.009 .000 .000 .000 .000 .000 .000 .000 .011 .011 .012 .000 .000 .000 .000 .000 .000 1.000
par_21 .000 .000 .000 .386 .280 .372 .000 .000 .000 .000 -.275 -.278 -.288 .000 .000 .000 .000 .000 .000 -.005 1.000
par_22 .000 .000 .000 .000 .000 .000 .997 .000 .000 .000 -.006 -.006 -.006 .000 .000 .000 .000 .000 .000 .000 .003 1.000
par_23 .029 .043 .048 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.108 -.126 -.114 .000 .000 .000 .067 .000 .000 1.000
par_24 .000 .000 .000 .182 .132 .175 .000 .000 .001 .000 .000 .000 .000 -.228 -.267 -.241 .000 .000 .000 .000 .146 .000 .040 1.000
par_25 .000 .000 .000 .000 .000 .000 .110 .000 -.002 .000 .000 .000 .000 -.001 -.001 -.001 .000 .000 .000 .000 .004 .115 .000 .010 1.000
par_26 .000 .000 .000 .001 .000 .000 .000 .271 .319 .283 .000 .000 .000 -.214 -.251 -.226 .000 .000 .000 .000 -.001 .000 .038 .066 .026 1.000
par_27 .000 .000 .000 .001 .000 .000 .000 .000 .005 .000 -.003 -.003 -.002 .148 .165 .155 -.129 -.131 -.129 -.050 -.031 .001 -.031 -.078 .037 -.105 1.000
par_28 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .000 .341 .344 .355 .000 .002 .000 -.516 -.527 -.517 .024 -.237 -.006 .002 -.006 -.013 -.002 -.190 1.000
par_29 .000 .000 .000 .000 .000 .000 .000 .571 .668 .599 -.257 -.259 -.269 .000 .000 .000 .000 .000 .000 -.006 .138 .003 .000 -.001 .007 .294 -.012 -.226 1.000
par_30 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_31 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .537 1.000
par_32 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .706 .464 1.000
par_33 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .749 .492 .646 1.000
par_34 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_35 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .673 1.000
par_36 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .504 .568 1.000
par_37 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .648 .730 .547 1.000
par_38 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_39 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .780 1.000
par_40 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
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 .360 1.000
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 .480 .509 1.000
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 .386 .409 .545 1.000
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 -.012 -.008 -.010 -.011 .309 .348 .260 .335 .059 .007 .331 .351 .468 .376 1.000
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 -.011 -.007 -.009 -.010 .277 .312 .234 .301 .053 .006 .297 .315 .420 .337 .568 1.000
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 -.011 -.007 -.009 -.010 .279 .314 .235 .303 .053 .006 .299 .317 .423 .340 .572 .513 1.000
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 -.011 -.007 -.009 -.010 .287 .323 .242 .311 .054 .006 .308 .326 .435 .349 .588 .528 .531 1.000
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 .079 .052 .068 .072 .152 .171 .128 .165 .001 .000 .116 .123 .164 .132 .191 .171 .172 .177 1.000
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 .081 .053 .070 .074 .155 .175 .131 .169 .001 .000 .119 .126 .168 .135 .195 .175 .176 .181 .461 1.000
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 .096 .063 .083 .088 .184 .208 .155 .200 .001 .000 .141 .149 .199 .160 .231 .207 .209 .215 .547 .559 1.000
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par_56 -.248 -.372 -.416 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .008 .000 .000 -.046 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
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par_58 .000 .000 .000 .000 .000 .000 -1.000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.997 .000 .000 -.110 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
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par_63 .236 .373 .437 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.008 .000 .000 .043 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.310 .000 .000 .000 .000 -.001 .000 1.000
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par_66 -.078 -.114 -.350 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 .000 .000 -.014 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .131 .000 .000 .000 .000 .000 .000 -.338 .002 .007 1.000
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par_69 .000 .000 .000 .010 -.124 .003 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .000 .000 -.001 .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 .006 .000 .000 -.003 .000 .000 .000 .000 .000 .000 -.012 -.049 1.000
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par_71 .000 .000 .000 .000 .000 .000 1.000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .997 .000 .000 .110 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -1.000 .000 -.084 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_72 .000 .000 .000 .000 .000 .000 -.983 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.983 .000 .000 -.108 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .986 .000 .083 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.986 1.000
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par_74 .000 .000 .000 .000 .000 .000 .000 -.143 .018 .001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .001 .000 -.003 .001 .003 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .007 -.020 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.007 1.000
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par_76 .000 .000 .000 .000 .000 .000 .000 .000 .024 -.156 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .002 .000 -.004 .001 .004 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .009 -.027 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.010 -.012 -.100 1.000
par_77 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .157 .159 .165 .000 .000 .000 .000 .000 .000 .005 -.084 -.002 .000 .000 -.002 .001 -.033 .152 -.079 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.159 .000 -.046 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .000 1.000
par_78 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.143 -.002 -.002 .000 .000 .000 .000 .000 .000 .000 .017 .000 .000 .000 -.001 .000 -.017 .005 .016 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.021 .000 -.024 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .000 -.028 1.000
par_79 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.002 -.145 -.002 .000 .000 .000 .000 .000 .000 .000 .017 .000 .000 .000 -.001 .000 -.018 .005 .016 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.022 .000 -.025 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .000 -.029 -.015 1.000
par_80 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.003 -.003 -.154 .000 .000 .000 .000 .000 .000 .000 .020 .000 .000 .000 -.001 .000 -.021 .006 .019 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.026 .000 -.029 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .000 -.033 -.018 -.018 1.000
par_81 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .197 .247 .209 .000 .000 .000 .000 .000 .000 -.036 -.076 .000 -.072 .056 -.002 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.221 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_82 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.200 .031 .004 .000 .000 .000 .000 .000 .000 .005 .011 .000 .010 .000 -.002 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .014 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.024 1.000
par_83 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .003 -.323 .016 .000 .000 .000 -.002 -.001 .000 .023 .050 .000 .047 .000 -.009 .000 .000 .000 .000 .000 .000 .000 .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 .063 -.002 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.001 .000 .000 .000 -.109 -.121 1.000
par_84 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .044 -.228 .000 .000 .000 .000 .000 .000 .007 .016 .000 .015 .000 -.003 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .001 .020 -.001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.034 -.038 -.172 1.000
par_85 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .099 .102 .099 .000 .000 .000 .000 .000 .000 .000 -.016 -.063 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.076 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 1.000
par_86 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.121 .014 .009 .000 .000 .000 .000 .000 .000 .000 .005 .019 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.017 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.023 1.000
par_87 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .012 -.133 .012 .000 .000 .000 .000 .000 .000 .000 .006 .026 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.023 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.031 -.123 1.000
par_88 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .009 .014 -.122 .000 .000 .000 .000 .000 .000 .000 .005 .019 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.018 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 -.024 -.093 -.125 1.000

Model Fit Summary

CMIN

Model NPAR CMIN DF P CMIN/DF
Default model 88 1369.791 289 .000 4.740
Saturated model 377 .000 0
Independence model 52 4822.603 325 .000 14.839

Baseline Comparisons

Model NFI
Delta1		 RFI
rho1		 IFI
Delta2		 TLI
rho2		 CFI
Default model .716 .681 .762 .730 .760
Saturated model 1.000 1.000 1.000
Independence model .000 .000 .000 .000 .000

Parsimony-Adjusted Measures

Model PRATIO PNFI PCFI
Default model .889 .637 .676
Saturated model .000 .000 .000
Independence model 1.000 .000 .000

NCP

Model NCP LO 90 HI 90
Default model 1080.791 969.355 1199.736
Saturated model .000 .000 .000
Independence model 4497.603 4276.578 4725.900

FMIN

Model FMIN F0 LO 90 HI 90
Default model 6.061 4.782 4.289 5.309
Saturated model .000 .000 .000 .000
Independence model 21.339 19.901 18.923 20.911

RMSEA

Model RMSEA LO 90 HI 90 PCLOSE
Default model .129 .122 .136 .000
Independence model .247 .241 .254 .000

AIC

Model AIC BCC BIC CAIC
Default model 1545.791 1569.671
Saturated model 754.000 856.302
Independence model 4926.603 4940.714

ECVI

Model ECVI LO 90 HI 90 MECVI
Default model 6.840 6.347 7.366 6.945
Saturated model 3.336 3.336 3.336 3.789
Independence model 21.799 20.821 22.809 21.862

HOELTER

Model HOELTER
.05		 HOELTER
.01
Default model 55 58
Independence model 18 19

Execution time summary

Minimization: .063
Miscellaneous: .559
Bootstrap: .000
Total: .622