“Mplus Second-Order CFA Example 5.6”的版本间的差异
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OUTPUT:STANDARDIZED; ! 报告标准化之后的结果，这是增加的命令语句</pre> | OUTPUT:STANDARDIZED; ! 报告标准化之后的结果，这是增加的命令语句</pre> | ||
==结果== | ==结果== | ||
| − | < | + | <pre>Mplus VERSION 7.4 |
MUTHEN & MUTHEN | MUTHEN & MUTHEN | ||
03/13/2017 1:53 PM | 03/13/2017 1:53 PM | ||
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
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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