Mplus VERSION 7.3
MUTHEN & MUTHEN
09/22/2014   5:48 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;



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


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.558E-02
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  17:48:45
        Ending Time:  17:48:45
       Elapsed Time:  00:00:00



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