Mplus VERSION 7
MUTHEN & MUTHEN
09/22/2012  10:51 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a path analysis
  	with categorical dependent variables
  DATA:	FILE IS ex3.12.dat;
  VARIABLE:	NAMES ARE u1-u3 x1-x3;
  	CATEGORICAL ARE u1-u3;
  MODEL:	u1 u2 ON x1 x2 x3;
  	u3 ON u1 u2 x2;



INPUT READING TERMINATED NORMALLY



this is an example of a path analysis
with categorical 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

  Binary and ordered categorical (ordinal)
   U1          U2          U3

Observed independent variables
   X1          X2          X3


Estimator                                                    WLSMV
Maximum number of iterations                                  1000
Convergence criterion                                    0.500D-04
Maximum number of steepest descent iterations                   20
Parameterization                                             DELTA

Input data file(s)
  ex3.12.dat

Input data format  FREE


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U1
      Category 1    0.398      199.000
      Category 2    0.226      113.000
      Category 3    0.376      188.000
    U2
      Category 1    0.528      264.000
      Category 2    0.472      236.000
    U3
      Category 1    0.440      220.000
      Category 2    0.126       63.000
      Category 3    0.156       78.000
      Category 4    0.278      139.000



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       15

Chi-Square Test of Model Fit

          Value                              0.936*
          Degrees of Freedom                     3
          P-Value                           0.8166

*   The chi-square value for MLM, MLMV, MLR, ULSMV, WLSM and WLSMV cannot be used
    for chi-square difference testing in the regular way.  MLM, MLR and WLSM
    chi-square difference testing is described on the Mplus website.  MLMV, WLSMV,
    and ULSMV difference testing is done using the DIFFTEST option.

RMSEA (Root Mean Square Error Of Approximation)

          Estimate                           0.000
          90 Percent C.I.                    0.000  0.046
          Probability RMSEA <= .05           0.961

CFI/TLI

          CFI                                1.000
          TLI                                1.010

Chi-Square Test of Model Fit for the Baseline Model

          Value                            875.406
          Degrees of Freedom                    12
          P-Value                           0.0000

WRMR (Weighted Root Mean Square Residual)

          Value                              0.213



MODEL RESULTS

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

 U1       ON
    X1                 2.662      0.197     13.505      0.000
    X2                 1.719      0.129     13.312      0.000
    X3                 0.928      0.104      8.962      0.000

 U2       ON
    X1                 0.920      0.177      5.212      0.000
    X2                 2.132      0.311      6.866      0.000
    X3                 3.553      0.463      7.673      0.000

 U3       ON
    U1                 0.588      0.050     11.698      0.000
    U2                -0.460      0.064     -7.233      0.000
    X2                 2.227      0.168     13.223      0.000

 Thresholds
    U1$1              -0.877      0.108     -8.095      0.000
    U1$2               1.101      0.115      9.552      0.000
    U2$1               0.111      0.114      0.972      0.331
    U3$1              -0.502      0.098     -5.121      0.000
    U3$2               0.463      0.093      4.960      0.000
    U3$3               1.696      0.127     13.381      0.000


R-SQUARE

    Observed                   Residual
    Variable        Estimate   Variance

    U1                 0.926      1.000
    U2                 0.954      1.000
    U3                 0.951      0.442


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.309E-02
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  22:51:43
        Ending Time:  22:51:43
       Elapsed Time:  00:00:00



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