Mplus VERSION 7.2
MUTHEN & MUTHEN
05/07/2014   2:40 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a two-group twin
  	model for categorical outcomes using parameter
      constraints
  DATA:	FILE = ex5.22.dat;
  VARIABLE:	NAMES = u1 u2 g;
  	GROUPING = g(1=mz 2=dz);
  	CATEGORICAL = u1 u2;
  MODEL:	[u1$1-u2$1](1);
  	u1 WITH u2(covmz);
  MODEL dz:	u1 WITH u2(covdz);
  MODEL CONSTRAINT:
  	NEW(a c e h);
  	covmz = a**2 + c**2;
  	covdz = 0.5*a**2 + c**2;
  	e = 1 - (a**2 + c**2);
  	h = a**2/1;



INPUT READING TERMINATED NORMALLY



this is an example of a two-group twin
model for categorical outcomes using parameter
constraints

SUMMARY OF ANALYSIS

Number of groups                                                 2
Number of observations
   Group MZ                                                   1000
   Group DZ                                                   1000
   Total sample size                                          2000

Number of dependent variables                                    2
Number of independent variables                                  0
Number of continuous latent variables                            0

Observed dependent variables

  Binary and ordered categorical (ordinal)
   U1          U2

Variables with special functions

  Grouping variable     G

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)
  ex5.22.dat

Input data format  FREE


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

  Group MZ
    U1
      Category 1    0.502      502.000
      Category 2    0.498      498.000
    U2
      Category 1    0.494      494.000
      Category 2    0.506      506.000

  Group DZ
    U1
      Category 1    0.504      504.000
      Category 2    0.496      496.000
    U2
      Category 1    0.511      511.000
      Category 2    0.489      489.000



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                        3

Chi-Square Test of Model Fit

          Value                              0.905*
          Degrees of Freedom                     3
          P-Value                           0.8242

Chi-Square Contribution From Each Group

          MZ                                 0.476
          DZ                                 0.429

*   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  0.032
          Probability RMSEA <= .05           0.992

CFI/TLI

          CFI                                1.000
          TLI                                1.001

Chi-Square Test of Model Fit for the Baseline Model

          Value                            952.816
          Degrees of Freedom                     2
          P-Value                           0.0000

WRMR (Weighted Root Mean Square Residual)

          Value                              0.442



MODEL RESULTS

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

Group MZ

 U1       WITH
    U2                 0.771      0.026     29.391      0.000

 Thresholds
    U1$1               0.007      0.024      0.292      0.770
    U2$1               0.007      0.024      0.292      0.770

Group DZ

 U1       WITH
    U2                 0.411      0.044      9.437      0.000

 Thresholds
    U1$1               0.007      0.024      0.292      0.770
    U2$1               0.007      0.024      0.292      0.770

New/Additional Parameters
    A                  0.848      0.060     14.123      0.000
    C                  0.228      0.199      1.146      0.252
    E                  0.229      0.026      8.744      0.000
    H                  0.719      0.102      7.061      0.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.469E-02
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  14:40:40
        Ending Time:  14:40:40
       Elapsed Time:  00:00:00



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