Mplus Second-Order CFA Example 5.6
来自OBHRM百科
Lichaoping（讨论 | 贡献）2017年3月13日 (一) 13:54的版本
示意图
代码与注释
TITLE: this is an example of a second-order factor analysis ! 这是标题
DATA: FILE IS ex5.6.dat; ! 读数据文件
VARIABLE: NAMES ARE y1-y12; ! 数据文件中有12个变量，命名y1-y12
MODEL: f1 BY y1-y3; ! 定义第1个因素，该因素的测量指标有：y1,y2,y3。
f2 BY y4-y6; ! 定义第2个因素，该因素的测量指标有：y4,y5,y6。
f3 BY y7-y9; ! 定义第3个因素，该因素的测量指标有：y7,y8,y9。
f4 BY y10-y12; ! 定义第4个因素，该因素的测量指标有：y10,y11,y12。
f5 BY f1-f4; ! 二阶因素f5
OUTPUT:STANDARDIZED; ! 报告标准化之后的结果，这是增加的命令语句
结果
</pre>Mplus VERSION 7.4 MUTHEN & MUTHEN 03/13/2017 1:53 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a second-order factor analysis
DATA: FILE IS ex5.6.dat;
VARIABLE: NAMES ARE y1-y12;
MODEL: f1 BY y1-y3;
f2 BY y4-y6;
f3 BY y7-y9;
f4 BY y10-y12;
f5 BY f1-f4;
OUTPUT:STANDARDIZED;
INPUT READING TERMINATED NORMALLY
this is an example of a second-order factor analysis
SUMMARY OF ANALYSIS
Number of groups 1 Number of observations 500
Number of dependent variables 12 Number of independent variables 0 Number of continuous latent variables 5
Observed dependent variables
Continuous Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 Y11 Y12
Continuous latent variables
F1 F2 F3 F4 F5
Estimator ML
Information matrix OBSERVED
Maximum number of iterations 1000
Convergence criterion 0.500D-04
Maximum number of steepest descent iterations 20
Input data file(s)
ex5.6.dat
Input data format FREE
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 40
Loglikelihood
H0 Value -7211.373
H1 Value -7188.001
Information Criteria
Akaike (AIC) 14502.746
Bayesian (BIC) 14671.330
Sample-Size Adjusted BIC 14544.368
(n* = (n + 2) / 24)
Chi-Square Test of Model Fit
Value 46.743
Degrees of Freedom 50
P-Value 0.6049
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.026
Probability RMSEA <= .05 1.000
CFI/TLI
CFI 1.000
TLI 1.001
Chi-Square Test of Model Fit for the Baseline Model
Value 4012.035
Degrees of Freedom 66
P-Value 0.0000
SRMR (Standardized Root Mean Square Residual)
Value 0.019
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
F1 BY Y1 1.000 0.000 999.000 999.000 Y2 0.760 0.031 24.275 0.000 Y3 0.669 0.030 22.309 0.000
F2 BY Y4 1.000 0.000 999.000 999.000 Y5 0.718 0.030 23.976 0.000 Y6 0.703 0.031 22.853 0.000
F3 BY Y7 1.000 0.000 999.000 999.000 Y8 0.702 0.026 26.955 0.000 Y9 0.691 0.026 26.764 0.000
F4 BY Y10 1.000 0.000 999.000 999.000 Y11 0.742 0.029 25.350 0.000 Y12 0.669 0.029 23.461 0.000
F5 BY F1 1.000 0.000 999.000 999.000 F2 0.944 0.148 6.397 0.000 F3 1.168 0.179 6.516 0.000 F4 0.854 0.139 6.142 0.000
Intercepts Y1 0.011 0.059 0.183 0.855 Y2 0.028 0.046 0.617 0.537 Y3 0.005 0.043 0.109 0.913 Y4 0.100 0.060 1.652 0.099 Y5 0.078 0.045 1.730 0.084 Y6 0.076 0.046 1.671 0.095 Y7 0.024 0.061 0.390 0.697 Y8 0.025 0.046 0.545 0.585 Y9 0.034 0.046 0.741 0.458 Y10 -0.016 0.062 -0.261 0.794 Y11 0.010 0.047 0.202 0.840 Y12 0.006 0.045 0.134 0.894
Variances F5 0.464 0.100 4.657 0.000
Residual Variances Y1 0.348 0.043 8.132 0.000 Y2 0.251 0.027 9.465 0.000 Y3 0.320 0.026 12.271 0.000 Y4 0.366 0.045 8.187 0.000 Y5 0.268 0.026 10.303 0.000 Y6 0.330 0.028 11.636 0.000 Y7 0.272 0.038 7.094 0.000 Y8 0.282 0.025 11.445 0.000 Y9 0.276 0.024 11.416 0.000 Y10 0.362 0.045 8.107 0.000 Y11 0.266 0.027 9.854 0.000 Y12 0.323 0.027 11.991 0.000 F1 0.913 0.103 8.855 0.000 F2 1.036 0.107 9.672 0.000 F3 0.984 0.119 8.237 0.000 F4 1.213 0.115 10.567 0.000
STANDARDIZED MODEL RESULTS
STDYX Standardization
Two-Tailed
Estimate S.E. Est./S.E. P-Value
F1 BY Y1 0.894 0.015 59.864 0.000 Y2 0.872 0.016 55.160 0.000 Y3 0.811 0.019 43.281 0.000
F2 BY Y4 0.894 0.015 60.275 0.000 Y5 0.858 0.016 52.512 0.000 Y6 0.828 0.018 46.167 0.000
F3 BY Y7 0.925 0.012 79.008 0.000 Y8 0.859 0.015 57.876 0.000 Y9 0.858 0.015 57.175 0.000
F4 BY Y10 0.900 0.014 64.368 0.000 Y11 0.873 0.015 57.629 0.000 Y12 0.826 0.018 46.877 0.000
F5 BY F1 0.580 0.053 10.851 0.000 F2 0.534 0.053 10.096 0.000 F3 0.626 0.053 11.779 0.000 F4 0.467 0.054 8.658 0.000
Intercepts Y1 0.008 0.045 0.183 0.855 Y2 0.028 0.045 0.617 0.537 Y3 0.005 0.045 0.109 0.913 Y4 0.074 0.045 1.650 0.099 Y5 0.077 0.045 1.728 0.084 Y6 0.075 0.045 1.668 0.095 Y7 0.017 0.045 0.390 0.697 Y8 0.024 0.045 0.545 0.585 Y9 0.033 0.045 0.741 0.459 Y10 -0.012 0.045 -0.261 0.794 Y11 0.009 0.045 0.202 0.840 Y12 0.006 0.045 0.134 0.894
Variances F5 1.000 0.000 999.000 999.000
Residual Variances Y1 0.202 0.027 7.557 0.000 Y2 0.240 0.028 8.689 0.000 Y3 0.342 0.030 11.247 0.000 Y4 0.201 0.026 7.601 0.000 Y5 0.264 0.028 9.403 0.000 Y6 0.315 0.030 10.621 0.000 Y7 0.144 0.022 6.634 0.000 Y8 0.261 0.026 10.236 0.000 Y9 0.263 0.026 10.225 0.000 Y10 0.189 0.025 7.516 0.000 Y11 0.238 0.026 8.981 0.000 Y12 0.317 0.029 10.901 0.000 F1 0.663 0.062 10.679 0.000 F2 0.714 0.057 12.629 0.000 F3 0.609 0.066 9.155 0.000 F4 0.782 0.050 15.527 0.000
STDY Standardization
Two-Tailed
Estimate S.E. Est./S.E. P-Value
F1 BY Y1 0.894 0.015 59.864 0.000 Y2 0.872 0.016 55.160 0.000 Y3 0.811 0.019 43.281 0.000
F2 BY Y4 0.894 0.015 60.275 0.000 Y5 0.858 0.016 52.512 0.000 Y6 0.828 0.018 46.167 0.000
F3 BY Y7 0.925 0.012 79.008 0.000 Y8 0.859 0.015 57.876 0.000 Y9 0.858 0.015 57.175 0.000
F4 BY Y10 0.900 0.014 64.368 0.000 Y11 0.873 0.015 57.629 0.000 Y12 0.826 0.018 46.877 0.000
F5 BY F1 0.580 0.053 10.851 0.000 F2 0.534 0.053 10.096 0.000 F3 0.626 0.053 11.779 0.000 F4 0.467 0.054 8.658 0.000
Intercepts Y1 0.008 0.045 0.183 0.855 Y2 0.028 0.045 0.617 0.537 Y3 0.005 0.045 0.109 0.913 Y4 0.074 0.045 1.650 0.099 Y5 0.077 0.045 1.728 0.084 Y6 0.075 0.045 1.668 0.095 Y7 0.017 0.045 0.390 0.697 Y8 0.024 0.045 0.545 0.585 Y9 0.033 0.045 0.741 0.459 Y10 -0.012 0.045 -0.261 0.794 Y11 0.009 0.045 0.202 0.840 Y12 0.006 0.045 0.134 0.894
Variances F5 1.000 0.000 999.000 999.000
Residual Variances Y1 0.202 0.027 7.557 0.000 Y2 0.240 0.028 8.689 0.000 Y3 0.342 0.030 11.247 0.000 Y4 0.201 0.026 7.601 0.000 Y5 0.264 0.028 9.403 0.000 Y6 0.315 0.030 10.621 0.000 Y7 0.144 0.022 6.634 0.000 Y8 0.261 0.026 10.236 0.000 Y9 0.263 0.026 10.225 0.000 Y10 0.189 0.025 7.516 0.000 Y11 0.238 0.026 8.981 0.000 Y12 0.317 0.029 10.901 0.000 F1 0.663 0.062 10.679 0.000 F2 0.714 0.057 12.629 0.000 F3 0.609 0.066 9.155 0.000 F4 0.782 0.050 15.527 0.000
STD Standardization
Two-Tailed
Estimate S.E. Est./S.E. P-Value
F1 BY Y1 1.174 0.048 24.382 0.000 Y2 0.892 0.038 23.520 0.000 Y3 0.785 0.037 21.235 0.000
F2 BY Y4 1.204 0.049 24.412 0.000 Y5 0.864 0.038 23.002 0.000 Y6 0.847 0.039 21.825 0.000
F3 BY Y7 1.272 0.048 26.282 0.000 Y8 0.893 0.038 23.433 0.000 Y9 0.879 0.038 23.359 0.000
F4 BY Y10 1.245 0.050 24.845 0.000 Y11 0.924 0.039 23.727 0.000 Y12 0.834 0.038 21.875 0.000
F5 BY F1 0.580 0.053 10.851 0.000 F2 0.534 0.053 10.096 0.000 F3 0.626 0.053 11.779 0.000 F4 0.467 0.054 8.658 0.000
Intercepts Y1 0.011 0.059 0.183 0.855 Y2 0.028 0.046 0.617 0.537 Y3 0.005 0.043 0.109 0.913 Y4 0.100 0.060 1.652 0.099 Y5 0.078 0.045 1.730 0.084 Y6 0.076 0.046 1.671 0.095 Y7 0.024 0.061 0.390 0.697 Y8 0.025 0.046 0.545 0.585 Y9 0.034 0.046 0.741 0.458 Y10 -0.016 0.062 -0.261 0.794 Y11 0.010 0.047 0.202 0.840 Y12 0.006 0.045 0.134 0.894
Variances F5 1.000 0.000 999.000 999.000
Residual Variances Y1 0.348 0.043 8.132 0.000 Y2 0.251 0.027 9.465 0.000 Y3 0.320 0.026 12.271 0.000 Y4 0.366 0.045 8.187 0.000 Y5 0.268 0.026 10.303 0.000 Y6 0.330 0.028 11.636 0.000 Y7 0.272 0.038 7.094 0.000 Y8 0.282 0.025 11.445 0.000 Y9 0.276 0.024 11.416 0.000 Y10 0.362 0.045 8.107 0.000 Y11 0.266 0.027 9.854 0.000 Y12 0.323 0.027 11.991 0.000 F1 0.663 0.062 10.679 0.000 F2 0.714 0.057 12.629 0.000 F3 0.609 0.066 9.155 0.000 F4 0.782 0.050 15.527 0.000
R-SQUARE
Observed Two-Tailed Variable Estimate S.E. Est./S.E. P-Value
Y1 0.798 0.027 29.932 0.000 Y2 0.760 0.028 27.580 0.000 Y3 0.658 0.030 21.641 0.000 Y4 0.799 0.026 30.138 0.000 Y5 0.736 0.028 26.256 0.000 Y6 0.685 0.030 23.083 0.000 Y7 0.856 0.022 39.504 0.000 Y8 0.739 0.026 28.938 0.000 Y9 0.737 0.026 28.588 0.000 Y10 0.811 0.025 32.184 0.000 Y11 0.762 0.026 28.815 0.000 Y12 0.683 0.029 23.439 0.000
Latent Two-Tailed Variable Estimate S.E. Est./S.E. P-Value
F1 0.337 0.062 5.425 0.000 F2 0.286 0.057 5.048 0.000 F3 0.391 0.066 5.889 0.000 F4 0.218 0.050 4.329 0.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.558E-02
(ratio of smallest to largest eigenvalue)
DIAGRAM INFORMATION
Use View Diagram under the Diagram menu in the Mplus Editor to view the diagram. If running Mplus from the Mplus Diagrammer, the diagram opens automatically.
Diagram output c:\program files\mplus\mplus examples\user's guide examples\mptext1.dgm
Beginning Time: 13:53:30
Ending Time: 13:53:31
Elapsed Time: 00:00:01
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