“Mplus Path Analysis Example 3.11”的版本间的差异
Lichaoping(讨论 | 贡献) (→代码与注释) |
|||
第9行: | 第9行: | ||
y3 ON y1 y2 x2; ! x2,y1,y2到y3的回归 | y3 ON y1 y2 x2; ! x2,y1,y2到y3的回归 | ||
OUTPUT: STANDARDIZED; ! 结果:标准化结果。</pre> | OUTPUT: STANDARDIZED; ! 结果:标准化结果。</pre> | ||
+ | |||
+ | ==结果== | ||
+ | Mplus VERSION 7.4 | ||
+ | MUTHEN & MUTHEN | ||
+ | 03/21/2017 9:59 PM | ||
+ | |||
+ | INPUT INSTRUCTIONS | ||
+ | |||
+ | TITLE: this is an example of a path analysis ! 标题 | ||
+ | with continuous dependent variables | ||
+ | DATA: FILE IS E:\2016\Mplus\MPlus+7.4+64位\Mplus Examples\User's Guide Examples\ex3.11.da | ||
+ | VARIABLE:NAMES ARE y1-y3 x1-x3; ! 数据文件中变量的名称,按顺序:y1,y2,y3,x1, | ||
+ | MODEL: y1 y2 ON x1 x2 x3; ! x1,x2,x3分别到y1,y2的回归 | ||
+ | y3 ON y1 y2 x2; ! x2,y1,y2到y3的回归 | ||
+ | OUTPUT: STANDARDIZED; ! 结果:标准化结果。 | ||
+ | |||
+ | |||
+ | |||
+ | *** WARNING | ||
+ | Input line exceeded 90 characters. Some input may be truncated. | ||
+ | DATA: FILE IS E:\2016\Mplus\MPlus+7.4+64位\Mplus Examples\User's Guide Examples\ex3.11.dat | ||
+ | *** WARNING | ||
+ | Input line exceeded 90 characters. Some input may be truncated. | ||
+ | VARIABLE:NAMES ARE y1-y3 x1-x3; ! 数据文件中变量的名称,按顺序:y1,y2,y3,x1,x | ||
+ | *** WARNING in DATA command | ||
+ | Statement not terminated by a semicolon: | ||
+ | FILE IS E:\2016\Mplus\MPlus+7.4+64位\Mplus Examples\User's Guide Examples\ex3.11.dat | ||
+ | 3 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS | ||
+ | |||
+ | |||
+ | |||
+ | this is an example of a path analysis | ||
+ | with continuous dependent variables | ||
+ | |||
+ | SUMMARY OF ANALYSIS | ||
+ | |||
+ | Number of groups 1 | ||
+ | Number of observations 500 | ||
+ | |||
+ | Number of dependent variables 3 | ||
+ | Number of independent variables 3 | ||
+ | Number of continuous latent variables 0 | ||
+ | |||
+ | Observed dependent variables | ||
+ | |||
+ | Continuous | ||
+ | Y1 Y2 Y3 | ||
+ | |||
+ | Observed independent variables | ||
+ | X1 X2 X3 | ||
+ | |||
+ | |||
+ | 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) | ||
+ | E:\2016\Mplus\MPlus+7.4+64位\Mplus Examples\User's Guide Examples\ex3.11.dat | ||
+ | |||
+ | Input data format FREE | ||
+ | |||
+ | |||
+ | |||
+ | THE MODEL ESTIMATION TERMINATED NORMALLY | ||
+ | |||
+ | |||
+ | |||
+ | MODEL FIT INFORMATION | ||
+ | |||
+ | Number of Free Parameters 15 | ||
+ | |||
+ | Loglikelihood | ||
+ | |||
+ | H0 Value -2364.002 | ||
+ | H1 Value -2363.623 | ||
+ | |||
+ | Information Criteria | ||
+ | |||
+ | Akaike (AIC) 4758.004 | ||
+ | Bayesian (BIC) 4821.223 | ||
+ | Sample-Size Adjusted BIC 4773.612 | ||
+ | (n* = (n + 2) / 24) | ||
+ | |||
+ | Chi-Square Test of Model Fit | ||
+ | |||
+ | Value 0.757 | ||
+ | Degrees of Freedom 3 | ||
+ | P-Value 0.8598 | ||
+ | |||
+ | RMSEA (Root Mean Square Error Of Approximation) | ||
+ | |||
+ | Estimate 0.000 | ||
+ | 90 Percent C.I. 0.000 0.040 | ||
+ | Probability RMSEA <= .05 0.972 | ||
+ | |||
+ | CFI/TLI | ||
+ | |||
+ | CFI 1.000 | ||
+ | TLI 1.002 | ||
+ | |||
+ | Chi-Square Test of Model Fit for the Baseline Model | ||
+ | |||
+ | Value 4107.449 | ||
+ | Degrees of Freedom 12 | ||
+ | P-Value 0.0000 | ||
+ | |||
+ | SRMR (Standardized Root Mean Square Residual) | ||
+ | |||
+ | Value 0.001 | ||
+ | |||
+ | |||
+ | |||
+ | MODEL RESULTS | ||
+ | |||
+ | Two-Tailed | ||
+ | Estimate S.E. Est./S.E. P-Value | ||
+ | |||
+ | Y1 ON | ||
+ | X1 0.992 0.043 22.979 0.000 | ||
+ | X2 2.001 0.045 44.618 0.000 | ||
+ | X3 3.052 0.045 68.274 0.000 | ||
+ | |||
+ | Y2 ON | ||
+ | X1 2.935 0.050 59.002 0.000 | ||
+ | X2 1.992 0.052 38.556 0.000 | ||
+ | X3 1.023 0.051 19.869 0.000 | ||
+ | |||
+ | Y3 ON | ||
+ | Y1 0.507 0.020 25.491 0.000 | ||
+ | Y2 0.746 0.020 37.914 0.000 | ||
+ | X2 1.046 0.072 14.540 0.000 | ||
+ | |||
+ | Intercepts | ||
+ | Y1 -1.064 0.046 -23.059 0.000 | ||
+ | Y2 -0.042 0.053 -0.784 0.433 | ||
+ | Y3 1.068 0.063 17.093 0.000 | ||
+ | |||
+ | Residual Variances | ||
+ | Y1 1.061 0.067 15.811 0.000 | ||
+ | Y2 1.408 0.089 15.811 0.000 | ||
+ | Y3 1.717 0.109 15.811 0.000 | ||
+ | |||
+ | |||
+ | STANDARDIZED MODEL RESULTS | ||
+ | |||
+ | |||
+ | STDYX Standardization | ||
+ | |||
+ | Two-Tailed | ||
+ | Estimate S.E. Est./S.E. P-Value | ||
+ | |||
+ | Y1 ON | ||
+ | X1 0.254 0.015 16.801 0.000 | ||
+ | X2 0.495 0.020 24.957 0.000 | ||
+ | X3 0.758 0.020 37.078 0.000 | ||
+ | |||
+ | Y2 ON | ||
+ | X1 0.759 0.021 35.491 0.000 | ||
+ | X2 0.497 0.021 23.938 0.000 | ||
+ | X3 0.256 0.016 15.680 0.000 | ||
+ | |||
+ | Y3 ON | ||
+ | Y1 0.375 0.016 23.022 0.000 | ||
+ | Y2 0.547 0.016 34.161 0.000 | ||
+ | X2 0.192 0.014 13.462 0.000 | ||
+ | |||
+ | Intercepts | ||
+ | Y1 -0.255 0.014 -18.599 0.000 | ||
+ | Y2 -0.010 0.013 -0.784 0.433 | ||
+ | Y3 0.190 0.012 15.238 0.000 | ||
+ | |||
+ | Residual Variances | ||
+ | Y1 0.061 0.005 11.537 0.000 | ||
+ | Y2 0.082 0.007 11.671 0.000 | ||
+ | Y3 0.054 0.005 11.497 0.000 | ||
+ | |||
+ | |||
+ | STDY Standardization | ||
+ | |||
+ | Two-Tailed | ||
+ | Estimate S.E. Est./S.E. P-Value | ||
+ | |||
+ | Y1 ON | ||
+ | X1 0.238 0.012 19.425 0.000 | ||
+ | X2 0.479 0.017 28.186 0.000 | ||
+ | X3 0.731 0.023 32.092 0.000 | ||
+ | |||
+ | Y2 ON | ||
+ | X1 0.710 0.022 32.309 0.000 | ||
+ | X2 0.482 0.018 27.283 0.000 | ||
+ | X3 0.247 0.014 17.668 0.000 | ||
+ | |||
+ | Y3 ON | ||
+ | Y1 0.375 0.016 23.022 0.000 | ||
+ | Y2 0.547 0.016 34.161 0.000 | ||
+ | X2 0.186 0.014 13.468 0.000 | ||
+ | |||
+ | Intercepts | ||
+ | Y1 -0.255 0.014 -18.599 0.000 | ||
+ | Y2 -0.010 0.013 -0.784 0.433 | ||
+ | Y3 0.190 0.012 15.238 0.000 | ||
+ | |||
+ | Residual Variances | ||
+ | Y1 0.061 0.005 11.537 0.000 | ||
+ | Y2 0.082 0.007 11.671 0.000 | ||
+ | Y3 0.054 0.005 11.497 0.000 | ||
+ | |||
+ | |||
+ | STD Standardization | ||
+ | |||
+ | Two-Tailed | ||
+ | Estimate S.E. Est./S.E. P-Value | ||
+ | |||
+ | Y1 ON | ||
+ | X1 0.992 0.043 22.979 0.000 | ||
+ | X2 2.001 0.045 44.618 0.000 | ||
+ | X3 3.052 0.045 68.274 0.000 | ||
+ | |||
+ | Y2 ON | ||
+ | X1 2.935 0.050 59.002 0.000 | ||
+ | X2 1.992 0.052 38.556 0.000 | ||
+ | X3 1.023 0.051 19.869 0.000 | ||
+ | |||
+ | Y3 ON | ||
+ | Y1 0.507 0.020 25.491 0.000 | ||
+ | Y2 0.746 0.020 37.914 0.000 | ||
+ | X2 1.046 0.072 14.540 0.000 | ||
+ | |||
+ | Intercepts | ||
+ | Y1 -1.064 0.046 -23.059 0.000 | ||
+ | Y2 -0.042 0.053 -0.784 0.433 | ||
+ | Y3 1.068 0.063 17.093 0.000 | ||
+ | |||
+ | Residual Variances | ||
+ | Y1 1.061 0.067 15.811 0.000 | ||
+ | Y2 1.408 0.089 15.811 0.000 | ||
+ | Y3 1.717 0.109 15.811 0.000 | ||
+ | |||
+ | |||
+ | R-SQUARE | ||
+ | |||
+ | Observed Two-Tailed | ||
+ | Variable Estimate S.E. Est./S.E. P-Value | ||
+ | |||
+ | Y1 0.939 0.005 177.949 0.000 | ||
+ | Y2 0.918 0.007 130.104 0.000 | ||
+ | Y3 0.946 0.005 201.127 0.000 | ||
+ | |||
+ | |||
+ | QUALITY OF NUMERICAL RESULTS | ||
+ | |||
+ | Condition Number for the Information Matrix 0.979E-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 | ||
+ | e:\2016\mplus\mptext2.dgm | ||
+ | |||
+ | Beginning Time: 21:59:39 | ||
+ | Ending Time: 21:59:40 | ||
+ | Elapsed Time: 00:00:01 | ||
+ | |||
+ | |||
+ | |||
+ | MUTHEN & MUTHEN | ||
+ | 3463 Stoner Ave. | ||
+ | Los Angeles, CA 90066 | ||
+ | |||
+ | Tel: (310) 391-9971 | ||
+ | Fax: (310) 391-8971 | ||
+ | Web: www.StatModel.com | ||
+ | Support: Support@StatModel.com | ||
+ | |||
+ | Copyright (c) 1998-2015 Muthen & Muthen |
2017年3月21日 (二) 22:02的版本
示意图
代码与注释
TITLE: this is an example of a path analysis ! 标题 with continuous dependent variables DATA: FILE IS ex3.11.dat; ! 数据文件 VARIABLE:NAMES ARE y1-y3 x1-x3; ! 数据文件中变量的名称,按顺序:y1,y2,y3,x1,x2,x3 MODEL: y1 y2 ON x1 x2 x3; ! x1,x2,x3分别到y1,y2的回归 y3 ON y1 y2 x2; ! x2,y1,y2到y3的回归 OUTPUT: STANDARDIZED; ! 结果:标准化结果。
结果
Mplus VERSION 7.4 MUTHEN & MUTHEN 03/21/2017 9:59 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a path analysis ! 标题 with continuous dependent variables DATA: FILE IS E:\2016\Mplus\MPlus+7.4+64位\Mplus Examples\User's Guide Examples\ex3.11.da VARIABLE:NAMES ARE y1-y3 x1-x3; ! 数据文件中变量的名称,按顺序:y1,y2,y3,x1, MODEL: y1 y2 ON x1 x2 x3; ! x1,x2,x3分别到y1,y2的回归 y3 ON y1 y2 x2; ! x2,y1,y2到y3的回归 OUTPUT: STANDARDIZED; ! 结果:标准化结果。
- WARNING
Input line exceeded 90 characters. Some input may be truncated. DATA: FILE IS E:\2016\Mplus\MPlus+7.4+64位\Mplus Examples\User's Guide Examples\ex3.11.dat
- WARNING
Input line exceeded 90 characters. Some input may be truncated. VARIABLE:NAMES ARE y1-y3 x1-x3; ! 数据文件中变量的名称,按顺序:y1,y2,y3,x1,x
- WARNING in DATA command
Statement not terminated by a semicolon: FILE IS E:\2016\Mplus\MPlus+7.4+64位\Mplus Examples\User's Guide Examples\ex3.11.dat 3 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS
this is an example of a path analysis with continuous dependent variables
SUMMARY OF ANALYSIS
Number of groups 1 Number of observations 500
Number of dependent variables 3 Number of independent variables 3 Number of continuous latent variables 0
Observed dependent variables
Continuous Y1 Y2 Y3
Observed independent variables
X1 X2 X3
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)
E:\2016\Mplus\MPlus+7.4+64位\Mplus Examples\User's Guide Examples\ex3.11.dat
Input data format FREE
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 15
Loglikelihood
H0 Value -2364.002 H1 Value -2363.623
Information Criteria
Akaike (AIC) 4758.004 Bayesian (BIC) 4821.223 Sample-Size Adjusted BIC 4773.612 (n* = (n + 2) / 24)
Chi-Square Test of Model Fit
Value 0.757 Degrees of Freedom 3 P-Value 0.8598
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000 90 Percent C.I. 0.000 0.040 Probability RMSEA <= .05 0.972
CFI/TLI
CFI 1.000 TLI 1.002
Chi-Square Test of Model Fit for the Baseline Model
Value 4107.449 Degrees of Freedom 12 P-Value 0.0000
SRMR (Standardized Root Mean Square Residual)
Value 0.001
MODEL RESULTS
Two-Tailed Estimate S.E. Est./S.E. P-Value
Y1 ON X1 0.992 0.043 22.979 0.000 X2 2.001 0.045 44.618 0.000 X3 3.052 0.045 68.274 0.000
Y2 ON X1 2.935 0.050 59.002 0.000 X2 1.992 0.052 38.556 0.000 X3 1.023 0.051 19.869 0.000
Y3 ON Y1 0.507 0.020 25.491 0.000 Y2 0.746 0.020 37.914 0.000 X2 1.046 0.072 14.540 0.000
Intercepts Y1 -1.064 0.046 -23.059 0.000 Y2 -0.042 0.053 -0.784 0.433 Y3 1.068 0.063 17.093 0.000
Residual Variances Y1 1.061 0.067 15.811 0.000 Y2 1.408 0.089 15.811 0.000 Y3 1.717 0.109 15.811 0.000
STANDARDIZED MODEL RESULTS
STDYX Standardization
Two-Tailed Estimate S.E. Est./S.E. P-Value
Y1 ON X1 0.254 0.015 16.801 0.000 X2 0.495 0.020 24.957 0.000 X3 0.758 0.020 37.078 0.000
Y2 ON X1 0.759 0.021 35.491 0.000 X2 0.497 0.021 23.938 0.000 X3 0.256 0.016 15.680 0.000
Y3 ON Y1 0.375 0.016 23.022 0.000 Y2 0.547 0.016 34.161 0.000 X2 0.192 0.014 13.462 0.000
Intercepts Y1 -0.255 0.014 -18.599 0.000 Y2 -0.010 0.013 -0.784 0.433 Y3 0.190 0.012 15.238 0.000
Residual Variances Y1 0.061 0.005 11.537 0.000 Y2 0.082 0.007 11.671 0.000 Y3 0.054 0.005 11.497 0.000
STDY Standardization
Two-Tailed Estimate S.E. Est./S.E. P-Value
Y1 ON X1 0.238 0.012 19.425 0.000 X2 0.479 0.017 28.186 0.000 X3 0.731 0.023 32.092 0.000
Y2 ON X1 0.710 0.022 32.309 0.000 X2 0.482 0.018 27.283 0.000 X3 0.247 0.014 17.668 0.000
Y3 ON Y1 0.375 0.016 23.022 0.000 Y2 0.547 0.016 34.161 0.000 X2 0.186 0.014 13.468 0.000
Intercepts Y1 -0.255 0.014 -18.599 0.000 Y2 -0.010 0.013 -0.784 0.433 Y3 0.190 0.012 15.238 0.000
Residual Variances Y1 0.061 0.005 11.537 0.000 Y2 0.082 0.007 11.671 0.000 Y3 0.054 0.005 11.497 0.000
STD Standardization
Two-Tailed Estimate S.E. Est./S.E. P-Value
Y1 ON X1 0.992 0.043 22.979 0.000 X2 2.001 0.045 44.618 0.000 X3 3.052 0.045 68.274 0.000
Y2 ON X1 2.935 0.050 59.002 0.000 X2 1.992 0.052 38.556 0.000 X3 1.023 0.051 19.869 0.000
Y3 ON Y1 0.507 0.020 25.491 0.000 Y2 0.746 0.020 37.914 0.000 X2 1.046 0.072 14.540 0.000
Intercepts Y1 -1.064 0.046 -23.059 0.000 Y2 -0.042 0.053 -0.784 0.433 Y3 1.068 0.063 17.093 0.000
Residual Variances Y1 1.061 0.067 15.811 0.000 Y2 1.408 0.089 15.811 0.000 Y3 1.717 0.109 15.811 0.000
R-SQUARE
Observed Two-Tailed Variable Estimate S.E. Est./S.E. P-Value
Y1 0.939 0.005 177.949 0.000 Y2 0.918 0.007 130.104 0.000 Y3 0.946 0.005 201.127 0.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.979E-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 e:\2016\mplus\mptext2.dgm
Beginning Time: 21:59:39 Ending Time: 21:59:40 Elapsed Time: 00:00:01
MUTHEN & MUTHEN 3463 Stoner Ave. Los Angeles, CA 90066
Tel: (310) 391-9971 Fax: (310) 391-8971 Web: www.StatModel.com Support: Support@StatModel.com
Copyright (c) 1998-2015 Muthen & Muthen