Mplus CFA Example 5.1
来自OBHRM百科
Lichaoping（讨论 | 贡献）2017年2月28日 (二) 10:58的版本
示意图
代码与注释
| Mplus代码 | 注释 |
| TITLE: this is an example of a CFA with continuous factor indicators; |
!这是标题，总共两行内容，第一行 !第二行，想要多少行，就写多少行 |
结果
| Mplus代码 | 注释 |
| Mplus VERSION 7.4 MUTHEN & MUTHEN 02/28/2017 10:53 AM INPUT INSTRUCTIONS TITLE: this is an example of a CFA with ! 这是标题，总共两行内容，第一行 continuous factor indicators; ! 第二行，想要多少行，就写多少行 DATA: FILE IS ex5.1.dat; ! 读取数据文件，请确保文件名正确，另外文件的路 VARIABLE: NAMES ARE y1-y6; ! 读取数据，该数据文件中包括6个变量的数据，变 MODEL: f1 BY y1-y3; ! 定义第1个因素，该因素的测量指标有：y1,y2,y f2 BY y4-y6; ! 定义第2个因素，该因素的测量指标有：y4,y5,y6 *** WARNING Input line exceeded 90 characters. Some input may be truncated. DATA: FILE IS ex5.1.dat; ! 读取数据文件，请确保文件名正确，另外文件的路? *** WARNING Input line exceeded 90 characters. Some input may be truncated. VARIABLE: NAMES ARE y1-y6; ! 读取数据，该数据文件中包括6个变量的数据，变? *** WARNING Input line exceeded 90 characters. Some input may be truncated. MODEL: f1 BY y1-y3; ! 定义第1个因素，该因素的测量指标有：y1,y2,y3 3 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS this is an example of a CFA with continuous factor indicators; ! 第二行，想要多少行，就写多少行 SUMMARY OF ANALYSIS Number of groups 1 Number of observations 500 Number of dependent variables 6 Number of independent variables 0 Number of continuous latent variables 2 Observed dependent variables Continuous Y1 Y2 Y3 Y4 Y5 Y6 Continuous latent variables F1 F2 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) ex5.1.dat Input data format FREE THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 19 Loglikelihood H0 Value -4906.609 H1 Value -4904.661 Information Criteria Akaike (AIC) 9851.218 Bayesian (BIC) 9931.295 Sample-Size Adjusted BIC 9870.988 (n* = (n + 2) / 24) Chi-Square Test of Model Fit Value 3.896 Degrees of Freedom 8 P-Value 0.8664 RMSEA (Root Mean Square Error Of Approximation) Estimate 0.000 90 Percent C.I. 0.000 0.027 Probability RMSEA <= .05 0.995 CFI/TLI CFI 1.000 TLI 1.013 Chi-Square Test of Model Fit for the Baseline Model Value 596.921 Degrees of Freedom 15 P-Value 0.0000 SRMR (Standardized Root Mean Square Residual) Value 0.014 MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value F1 BY Y1 1.000 0.000 999.000 999.000 Y2 1.126 0.099 11.368 0.000 Y3 1.019 0.089 11.482 0.000 F2 BY Y4 1.000 0.000 999.000 999.000 Y5 1.059 0.129 8.199 0.000 Y6 0.897 0.105 8.531 0.000 F2 WITH F1 -0.030 0.052 -0.582 0.560 Intercepts Y1 -0.022 0.063 -0.354 0.723 Y2 0.026 0.062 0.410 0.682 Y3 0.035 0.062 0.555 0.579 Y4 -0.022 0.064 -0.350 0.726 Y5 -0.016 0.058 -0.271 0.786 Y6 0.048 0.058 0.824 0.410 Variances F1 0.907 0.125 7.254 0.000 F2 0.760 0.133 5.734 0.000 Residual Variances Y1 1.064 0.096 11.120 0.000 Y2 0.798 0.100 7.972 0.000 Y3 1.010 0.095 10.597 0.000 Y4 1.290 0.119 10.871 0.000 Y5 0.854 0.111 7.710 0.000 Y6 1.066 0.097 11.024 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.409E-01 (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\ex5.1.dgm Beginning Time: 10:53:53 Ending Time: 10:53:53 Elapsed Time: 00:00:00 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 | !这是标题，总共两行内容，第一行 !第二行，想要多少行，就写多少行 |
