Mplus VERSION 7.2
MUTHEN & MUTHEN
05/07/2014   2:41 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a linear growth
  	model for a categorical outcome using the
  	Theta parameterization
  DATA:	FILE IS ex6.5.dat;
  VARIABLE:	NAMES ARE u11-u14;
  	CATEGORICAL ARE u11-u14;
  ANALYSIS:	PARAMETERIZATION = THETA;
  MODEL:	i s | u11@0 u12@1 u13@2 u14@3;



INPUT READING TERMINATED NORMALLY



this is an example of a linear growth
model for a categorical outcome using the
Theta parameterization

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                         500

Number of dependent variables                                    4
Number of independent variables                                  0
Number of continuous latent variables                            2

Observed dependent variables

  Binary and ordered categorical (ordinal)
   U11         U12         U13         U14

Continuous latent variables
   I           S


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

Input data file(s)
  ex6.5.dat

Input data format  FREE


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U11
      Category 1    0.236      118.000
      Category 2    0.248      124.000
      Category 3    0.264      132.000
      Category 4    0.252      126.000
    U12
      Category 1    0.388      194.000
      Category 2    0.282      141.000
      Category 3    0.168       84.000
      Category 4    0.162       81.000
    U13
      Category 1    0.594      297.000
      Category 2    0.130       65.000
      Category 3    0.148       74.000
      Category 4    0.128       64.000
    U14
      Category 1    0.676      338.000
      Category 2    0.126       63.000
      Category 3    0.090       45.000
      Category 4    0.108       54.000



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       10

Chi-Square Test of Model Fit

          Value                             12.014*
          Degrees of Freedom                     8
          P-Value                           0.1506

*   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                           0.032
          90 Percent C.I.                    0.000  0.066
          Probability RMSEA <= .05           0.777

CFI/TLI

          CFI                                0.992
          TLI                                0.994

Chi-Square Test of Model Fit for the Baseline Model

          Value                            491.173
          Degrees of Freedom                     6
          P-Value                           0.0000

WRMR (Weighted Root Mean Square Residual)

          Value                              0.613



MODEL RESULTS

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

 I        |
    U11                1.000      0.000    999.000    999.000
    U12                1.000      0.000    999.000    999.000
    U13                1.000      0.000    999.000    999.000
    U14                1.000      0.000    999.000    999.000

 S        |
    U11                0.000      0.000    999.000    999.000
    U12                1.000      0.000    999.000    999.000
    U13                2.000      0.000    999.000    999.000
    U14                3.000      0.000    999.000    999.000

 S        WITH
    I                 -0.047      0.118     -0.400      0.689

 Means
    I                  0.000      0.000    999.000    999.000
    S                 -0.772      0.107     -7.189      0.000

 Thresholds
    U11$1             -1.144      0.152     -7.524      0.000
    U11$2             -0.071      0.078     -0.913      0.361
    U11$3              1.001      0.143      7.001      0.000
    U12$1             -1.144      0.152     -7.524      0.000
    U12$2             -0.071      0.078     -0.913      0.361
    U12$3              1.001      0.143      7.001      0.000
    U13$1             -1.144      0.152     -7.524      0.000
    U13$2             -0.071      0.078     -0.913      0.361
    U13$3              1.001      0.143      7.001      0.000
    U14$1             -1.144      0.152     -7.524      0.000
    U14$2             -0.071      0.078     -0.913      0.361
    U14$3              1.001      0.143      7.001      0.000

 Variances
    I                  1.451      0.500      2.900      0.004
    S                  0.313      0.135      2.312      0.021

 Residual Variances
    U11                1.000      0.000    999.000    999.000
    U12                1.334      0.409      3.264      0.001
    U13                2.417      0.688      3.513      0.000
    U14                3.330      1.005      3.311      0.001


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.314E-03
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  14:41:32
        Ending Time:  14:41:32
       Elapsed Time:  00:00:00



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