查看“Mplus CFA Example 5.1”的源代码

==示意图==

==代码与注释==
<pre>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;  ! 读数据文件，文件名要正确，文件路径与对应的分析程序在同一目录下；或标明绝对路径，比如：c:\mplus\ex5.1.dat。
VARIABLE: NAMES ARE y1-y6;    ! 读取数据，该数据文件中包括6个变量的数据，变量名称可以自己定。比如，可以是y1-y6，也可以是item1-item6
MODEL:    f1 BY y1-y3;        ! 定义第1个因素，该因素的测量指标有：y1,y2,y3。如果上面为item1-item6，则修改为item1-item3
          f2 BY y4-y6;        ! 定义第2个因素，该因素的测量指标有：y4,y5,y6</pre>

==结果==
<pre>
Mplus VERSION 7.4                                  ！ Mplus的版本信息
MUTHEN & MUTHEN                                    ！ Mplus作者信息
10/26/2015   7:54 PM                               ！ 分析时间

INPUT INSTRUCTIONS                                 ！输入的命令语言，会全部显示

  TITLE:	this is an example of a CFA with
  	continuous factor indicators
  DATA:	FILE IS ex5.1.dat;
  VARIABLE:	NAMES ARE y1-y6;
  MODEL:	f1 BY y1-y3;
  	f2 BY y4-y6;



INPUT READING TERMINATED NORMALLY



this is an example of a CFA with
continuous factor indicators

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)


     Beginning Time:  19:54:46
        Ending Time:  19:54:46
       Elapsed Time:  00:00:00



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