Mplus VERSION 5.1
MUTHEN & MUTHEN
05/05/2008   8:26 PM

INPUT INSTRUCTIONS

  TITLE:  cat3

          mimic with direct effects for dichotomous outcomes

  DATA: FILE IS wmimicd.dat;

  VARIABLE: NAMES ARE x1-x3 y1-y16;

          USEV = y6-y10 x4 x5 x6 x7;

          CATEGORICAL = y6-y10;

  DEFINE:  x4   =   89 - x1;
           x6  =  0; if (x2 eq 2) then x6 = 1;
           x7  =  0; if (x2 eq 1) then x7 = 1;
           x5 = 1; if (x3 eq 2) then x5 = 0;

  ANALYSIS:  TYPE = MEANSTRUCTURE;

  !        using meanstructure adds the thresholds for the
  !        dichotomous outcomes, but is not essential here

             ESTIMATOR = WLSMV;

  MODEL:  f1 BY y6-y10;
          f1 ON x4-x7;
          y6 ON x5;

  !        y6 ON x5 is the direct effect

  !        given that x variables are present, the analysis assumes
  !        conditional normality of latent response variables given the x's
  !        in line with probit analysis. this analysis makes less strong
  !        normality assumptions than using tetrachoric
  !        and biserial correlations.  Given that the model is fitted to
  !        estimates from probit regressions, the computations are, however,
  !        more time consuming than when x's are not present, especially
  !        for large sample sizes (as in this case) and a large number of
  !        outcome variables.




*** WARNING in ANALYSIS command
  Starting with Version 5, TYPE=MEANSTRUCTURE is the default for all
  analyses.  To remove means from the model, use
  MODEL=NOMEANSTRUCTURE in the ANALYSIS command.
   1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS



cat3

mimic with direct effects for dichotomous outcomes

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        5042

Number of dependent variables                                    5
Number of independent variables                                  4
Number of continuous latent variables                            1

Observed dependent variables

  Binary and ordered categorical (ordinal)
   Y6          Y7          Y8          Y9          Y10

Observed independent variables
   X4          X5          X6          X7

Continuous latent variables
   F1


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)
  wmimicd.dat

Input data format  FREE


SUMMARY OF CATEGORICAL DATA PROPORTIONS

    Y6
      Category 1    0.982
      Category 2    0.018
    Y7
      Category 1    0.972
      Category 2    0.028
    Y8
      Category 1    0.986
      Category 2    0.014
    Y9
      Category 1    0.989
      Category 2    0.011
    Y10
      Category 1    0.956
      Category 2    0.044



THE MODEL ESTIMATION TERMINATED NORMALLY



TESTS OF MODEL FIT

Chi-Square Test of Model Fit

          Value                             37.946*
          Degrees of Freedom                    17**
          P-Value                           0.0025

*   The chi-square value for MLM, MLMV, MLR, ULSMV, WLSM and WLSMV cannot be used
    for chi-square difference tests.  MLM, MLR and WLSM chi-square difference
    testing is described in the Mplus Technical Appendices at www.statmodel.com.
    See chi-square difference testing in the index of the Mplus User's Guide.

**  The degrees of freedom for MLMV, ULSMV and WLSMV are estimated according to
    a formula given in the Mplus Technical Appendices at www.statmodel.com.
    See degrees of freedom in the index of the Mplus User's Guide.

Chi-Square Test of Model Fit for the Baseline Model

          Value                           1857.836
          Degrees of Freedom                    17
          P-Value                           0.0000

CFI/TLI

          CFI                                0.989
          TLI                                0.989

Number of Free Parameters                       15

RMSEA (Root Mean Square Error Of Approximation)

          Estimate                           0.016

WRMR (Weighted Root Mean Square Residual)

          Value                              0.906



MODEL RESULTS

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

 F1       BY
    Y6                 1.000      0.000    999.000    999.000
    Y7                 1.071      0.051     20.864      0.000
    Y8                 1.079      0.053     20.418      0.000
    Y9                 1.036      0.055     18.734      0.000
    Y10                1.010      0.049     20.444      0.000

 F1       ON
    X4                -0.032      0.012     -2.716      0.007
    X5                 0.385      0.060      6.388      0.000
    X6                 0.081      0.059      1.371      0.170
    X7                 0.097      0.074      1.322      0.186

 Y6       ON
    X5                 0.311      0.103      3.012      0.003

 Thresholds
    Y6$1               1.243      0.566      2.195      0.028
    Y7$1               2.218      0.465      4.772      0.000
    Y8$1               1.688      0.629      2.686      0.007
    Y9$1               2.048      0.655      3.128      0.002
    Y10$1              0.345      0.399      0.865      0.387

 Residual Variances
    F1                 0.663      0.054     12.222      0.000


R-SQUARE

    Observed                   Residual
    Variable        Estimate   Variance

    Y6                 0.702      0.337
    Y7                 0.773      0.239
    Y8                 0.783      0.228
    Y9                 0.725      0.289
    Y10                0.691      0.323

     Latent
    Variable        Estimate

    F1                 0.065


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.151E-03
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  20:26:11
        Ending Time:  20:26:12
       Elapsed Time:  00:00:01



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