Introduction to Structural Equation Modeling with Latent Variables

Fit Summary of the LISMOD Model for Career Aspiration Analysis 3

Figure 54 shows the fit summary of the LISMOD model. All these fit index values match those from using the PATH model specification of the same model, as shown in Figure 48. Therefore, you are confident that the current LISMOD model specification is equivalent to the PATH model specification shown in the section Career Aspiration (Analysis 3).

Figure 54: Career Aspiration Analysis 3: Fit Summary of the LISMOD Model

Fit Summary
Chi-Square 12.0132
Chi-Square DF 13
Pr > Chi-Square 0.5266
Standardized RMR (SRMR) 0.0149
Adjusted GFI (AGFI) 0.9692
RMSEA Estimate 0.0000
Akaike Information Criterion 96.0132
Schwarz Bayesian Criterion 255.4476
Bentler Comparative Fit Index 1.0000


Estimation results are shown in Figure 55, Figure 56, and Figure 57, respectively for the measurement model for y, measurement model for x, and the structural model. These are the same estimation results as those from the equivalent PATH model specification in Figure 49. However, estimates in the LISMOD model are now arranged in the matrix form, with standard error estimates and t values shown.

Figure 55: Career Aspiration Analysis 3: Estimation of Measurement Model for y

_LAMBDAY_ Matrix: Estimate/StdErr/t-value/p-value
  R_Amb F_Amb
rea
1.0840
0.0942
11.5105
<.0001
[_Parm01]
0
 
 
 
 
roa
1.0000
 
 
 
 
0
 
 
 
 
foa
0
 
 
 
 
1.0000
 
 
 
 
fea
0
 
 
 
 
1.1163
0.0863
12.9394
<.0001
[_Parm02]

_THETAY_ Matrix: Estimate/StdErr/t-value/p-value
  rea roa foa fea
rea
0.3271
0.0545
5.9988
<.0001
[_Add07]
0
 
 
 
 
0
 
 
 
 
0.0231
0.0314
0.7355
0.4621
[_Parm13]
roa
0
 
 
 
 
0.4231
0.0524
8.0695
<.0001
[_Add08]
0.1121
0.0326
3.4399
0.000582
[_Parm14]
0
 
 
 
 
foa
0
 
 
 
 
0.1121
0.0326
3.4399
0.000582
[_Parm14]
0.4224
0.0473
8.9310
<.0001
[_Add09]
0
 
 
 
 
fea
0.0231
0.0314
0.7355
0.4621
[_Parm13]
0
 
 
 
 
0
 
 
 
 
0.2872
0.0480
5.9776
<.0001
[_Add10]


Figure 56: Career Aspiration Analysis 3: Estimation of Measurement Model for x

_LAMBDAX_ Matrix: Estimate/StdErr/t-value/p-value
  f_rpa f_riq f_rses f_fses f_fiq f_fpa
rpa
0.8370
 
 
 
0
 
 
 
0
 
 
 
0
 
 
 
0
 
 
 
0
 
 
 
riq
0
 
 
 
0.8940
 
 
 
0
 
 
 
0
 
 
 
0
 
 
 
0
 
 
 
rses
0
 
 
 
0
 
 
 
0.9490
 
 
 
0
 
 
 
0
 
 
 
0
 
 
 
fses
0
 
 
 
0
 
 
 
0
 
 
 
0.9490
 
 
 
0
 
 
 
0
 
 
 
fiq
0
 
 
 
0
 
 
 
0
 
 
 
0
 
 
 
0.8940
 
 
 
0
 
 
 
fpa
0
 
 
 
0
 
 
 
0
 
 
 
0
 
 
 
0
 
 
 
0.8370
 
 
 

_THETAX_ Matrix: Estimate/StdErr/t-value/p-value
  rpa riq rses fses fiq fpa
rpa
0.2958
0.0777
3.8057
0.000141
[_Add01]
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
riq
0
 
 
 
 
0.2087
0.0783
2.6652
0.007695
[_Add02]
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
rses
0
 
 
 
 
0
 
 
 
 
0.0989
0.0780
1.2671
0.2051
[_Add03]
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
fses
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
0.1032
0.0782
1.3195
0.1870
[_Add04]
0
 
 
 
 
0
 
 
 
 
fiq
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
0.1999
0.0767
2.6048
0.009192
[_Add05]
0
 
 
 
 
fpa
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
0
 
 
 
 
0.2999
0.0781
3.8409
0.000123
[_Add06]


Figure 57: Career Aspiration Analysis 3: Estimation of Structural Model

_BETA_ Matrix: Estimate/StdErr/t-value/p-value
  R_Amb F_Amb
R_Amb
0
 
 
 
 
0.1190
0.1140
1.0441
0.2964
[_Parm12]
F_Amb
0.1302
0.1207
1.0791
0.2805
[_Parm11]
0
 
 
 
 

_GAMMA_ Matrix: Estimate/StdErr/t-value/p-value
  f_rpa f_riq f_rses f_fses f_fiq f_fpa
R_Amb
0.1837
0.0504
3.6420
0.000271
[_Parm03]
0.2800
0.0614
4.5618
<.0001
[_Parm04]
0.2262
0.0522
4.3300
<.0001
[_Parm05]
0.0870
0.0548
1.5883
0.1122
[_Parm06]
0
 
 
 
 
0
 
 
 
 
F_Amb
0
 
 
 
 
0
 
 
 
 
0.0633
0.0522
1.2124
0.2254
[_Parm07]
0.2154
0.0512
4.2060
<.0001
[_Parm08]
0.3539
0.0674
5.2497
<.0001
[_Parm09]
0.1688
0.0493
3.4205
0.000625
[_Parm10]

_PSI_ Matrix: Estimate/StdErr/t-value/p-value
  R_Amb F_Amb
R_Amb
0.2542
0.0447
5.6874
<.0001
[_Add11]
-0.009355
0.0501
-0.1867
0.8519
[_Parm15]
F_Amb
-0.009355
0.0501
-0.1867
0.8519
[_Parm15]
0.1970
0.0381
5.1653
<.0001
[_Add12]

_PHI_ Matrix: Estimate/StdErr/t-value/p-value
  f_rpa f_riq f_rses f_fses f_fiq f_fpa
f_rpa
1.0000
 
 
 
 
0.2468
0.0752
3.2820
0.001031
[_Add13]
0.0618
0.0695
0.8903
0.3733
[_Add14]
0.0238
0.0695
0.3427
0.7318
[_Add16]
0.1085
0.0736
1.4742
0.1404
[_Add19]
0.1579
0.0787
2.0056
0.0449
[_Add23]
f_riq
0.2468
0.0752
3.2820
0.001031
[_Add13]
1.0000
 
 
 
 
0.2635
0.0669
3.9408
<.0001
[_Add15]
0.2214
0.0665
3.3298
0.000869
[_Add17]
0.4248
0.0722
5.8837
<.0001
[_Add20]
0.1308
0.0742
1.7639
0.0778
[_Add24]
f_rses
0.0618
0.0695
0.8903
0.3733
[_Add14]
0.2635
0.0669
3.9408
<.0001
[_Add15]
1.0000
 
 
 
 
0.3016
0.0636
4.7421
<.0001
[_Add18]
0.2725
0.0666
4.0914
<.0001
[_Add21]
0.1152
0.0698
1.6505
0.0988
[_Add25]
f_fses
0.0238
0.0695
0.3427
0.7318
[_Add16]
0.2214
0.0665
3.3298
0.000869
[_Add17]
0.3016
0.0636
4.7421
<.0001
[_Add18]
1.0000
 
 
 
 
0.3492
0.0677
5.1576
<.0001
[_Add22]
-0.0562
0.0697
-0.8065
0.4200
[_Add26]
f_fiq
0.1085
0.0736
1.4742
0.1404
[_Add19]
0.4248
0.0722
5.8837
<.0001
[_Add20]
0.2725
0.0666
4.0914
<.0001
[_Add21]
0.3492
0.0677
5.1576
<.0001
[_Add22]
1.0000
 
 
 
 
0.2787
0.0753
3.7008
0.000215
[_Add27]
f_fpa
0.1579
0.0787
2.0056
0.0449
[_Add23]
0.1308
0.0742
1.7639
0.0778
[_Add24]
0.1152
0.0698
1.6505
0.0988
[_Add25]
-0.0562
0.0697
-0.8065
0.4200
[_Add26]
0.2787
0.0753
3.7008
0.000215
[_Add27]
1.0000
 
 
 
 


Last updated: December 09, 2022