Mplus VERSION 7
MUTHEN & MUTHEN
09/22/2012  10:55 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a SEM with
  EFA and CFA factors with continuous factor indicators
  DATA:	FILE IS ex5.25.dat;
  VARIABLE:	NAMES ARE y1-y12;
  MODEL:	f1-f2 BY y1-y6 (*1);
  	f3 BY y7-y9;
  	f4 BY y10-y12;
  	f3 ON f1-f2;
  	f4 ON f3;



INPUT READING TERMINATED NORMALLY



this is an example of a SEM with
EFA and CFA factors with continuous factor indicators

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                            4

Observed dependent variables

  Continuous
   Y1          Y2          Y3          Y4          Y5          Y6
   Y7          Y8          Y9          Y10         Y11         Y12

Continuous latent variables
   F3          F4

  EFA factors
  *1:   F1          F2


Estimator                                                       ML
Rotation                                                    GEOMIN
Row standardization                                    CORRELATION
Type of rotation                                           OBLIQUE
Epsilon value                                               Varies
Information matrix                                        OBSERVED
Maximum number of iterations                                  1000
Convergence criterion                                    0.500D-04
Maximum number of steepest descent iterations                   20
Optimization Specifications for the Exploratory Factor Analysis
Rotation Algorithm
  Number of random starts                                       30
  Maximum number of iterations                               10000
  Derivative convergence criterion                       0.100D-04

Input data file(s)
  ex5.25.dat

Input data format  FREE



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       44

Loglikelihood

          H0 Value                       -6482.762
          H1 Value                       -6457.085

Information Criteria

          Akaike (AIC)                   13053.524
          Bayesian (BIC)                 13238.966
          Sample-Size Adjusted BIC       13099.308
            (n* = (n + 2) / 24)

Chi-Square Test of Model Fit

          Value                             51.353
          Degrees of Freedom                    46
          P-Value                           0.2720

RMSEA (Root Mean Square Error Of Approximation)

          Estimate                           0.015
          90 Percent C.I.                    0.000  0.034
          Probability RMSEA <= .05           1.000

CFI/TLI

          CFI                                0.999
          TLI                                0.998

Chi-Square Test of Model Fit for the Baseline Model

          Value                           4600.240
          Degrees of Freedom                    66
          P-Value                           0.0000

SRMR (Standardized Root Mean Square Residual)

          Value                              0.018



MODEL RESULTS

                                                    Two-Tailed
                    Estimate       S.E.  Est./S.E.    P-Value

 F1       BY
    Y1                 0.751      0.048     15.609      0.000
    Y2                 0.858      0.042     20.467      0.000
    Y3                 0.736      0.045     16.353      0.000
    Y4                 0.036      0.051      0.711      0.477
    Y5                -0.028      0.049     -0.568      0.570
    Y6                 0.002      0.004      0.627      0.531

 F2       BY
    Y1                 0.034      0.045      0.755      0.450
    Y2                -0.002      0.016     -0.150      0.881
    Y3                -0.008      0.035     -0.220      0.826
    Y4                 0.763      0.050     15.367      0.000
    Y5                 0.810      0.048     16.837      0.000
    Y6                 0.802      0.041     19.461      0.000

 F3       BY
    Y7                 1.000      0.000    999.000    999.000
    Y8                 0.894      0.021     41.936      0.000
    Y9                 0.902      0.021     42.479      0.000

 F4       BY
    Y10                1.000      0.000    999.000    999.000
    Y11                0.734      0.028     26.424      0.000
    Y12                0.684      0.028     24.405      0.000

 F3       ON
    F1                 0.493      0.058      8.462      0.000
    F2                 0.721      0.057     12.752      0.000

 F4       ON
    F3                 0.546      0.032     16.975      0.000

 F2       WITH
    F1                 0.479      0.053      9.094      0.000

 Intercepts
    Y1                 0.008      0.044      0.183      0.855
    Y2                 0.031      0.045      0.688      0.491
    Y3                 0.006      0.043      0.146      0.884
    Y4                 0.075      0.045      1.659      0.097
    Y5                 0.070      0.044      1.592      0.111
    Y6                 0.070      0.046      1.530      0.126
    Y7                 0.059      0.060      0.983      0.326
    Y8                 0.061      0.055      1.115      0.265
    Y9                 0.069      0.055      1.253      0.210
    Y10                0.009      0.051      0.170      0.865
    Y11                0.024      0.039      0.616      0.538
    Y12                0.021      0.038      0.554      0.580

 Variances
    F1                 1.000      0.000    999.000    999.000
    F2                 1.000      0.000    999.000    999.000

 Residual Variances
    Y1                 0.376      0.034     11.064      0.000
    Y2                 0.290      0.035      8.239      0.000
    Y3                 0.406      0.034     11.817      0.000
    Y4                 0.408      0.035     11.742      0.000
    Y5                 0.329      0.033     10.046      0.000
    Y6                 0.393      0.035     11.073      0.000
    Y7                 0.183      0.019      9.796      0.000
    Y8                 0.191      0.017     11.269      0.000
    Y9                 0.181      0.017     10.812      0.000
    Y10                0.240      0.027      8.746      0.000
    Y11                0.183      0.017     10.791      0.000
    Y12                0.213      0.018     11.998      0.000
    F3                 0.527      0.049     10.644      0.000
    F4                 0.565      0.049     11.488      0.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.111E-01
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  22:55:32
        Ending Time:  22:55:32
       Elapsed Time:  00:00:00



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