Mplus Path Analysis Example 3.11
来自OBHRM百科
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 ex3.11.dat;
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 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 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
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