Mplus VERSION 7.2
MUTHEN & MUTHEN
05/07/2014   2:38 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a path analysis
  	with a combination of continuous and
  	categorical dependent variables
  DATA:	FILE IS ex3.14.dat;
  VARIABLE:	NAMES ARE y1 y2 u1 x1-x3;
  	CATEGORICAL IS u1;
  MODEL:	y1 y2 ON x1 x2 x3;
  	u1 ON y1 y2 x2;



INPUT READING TERMINATED NORMALLY



this is an example of a path analysis
with a combination of continuous and
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

  Continuous
   Y1          Y2

  Binary and ordered categorical (ordinal)
   U1

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)
  ex3.14.dat

Input data format  FREE


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U1
      Category 1    0.664      332.000
      Category 2    0.336      168.000



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       14

Chi-Square Test of Model Fit

          Value                              1.578*
          Degrees of Freedom                     3
          P-Value                           0.6644

*   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  0.059
          Probability RMSEA <= .05           0.915

CFI/TLI

          CFI                                1.000
          TLI                                1.009

Chi-Square Test of Model Fit for the Baseline Model

          Value                            670.933
          Degrees of Freedom                    12
          P-Value                           0.0000

WRMR (Weighted Root Mean Square Residual)

          Value                              0.265



MODEL RESULTS

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

 Y1       ON
    X1                 0.088      0.031      2.861      0.004
    X2                 0.201      0.032      6.271      0.000
    X3                 0.347      0.036      9.542      0.000

 Y2       ON
    X1                 0.275      0.023     12.053      0.000
    X2                 0.196      0.024      8.242      0.000
    X3                 0.105      0.024      4.369      0.000

 U1       ON
    Y1                 1.013      0.060     16.994      0.000
    Y2                -1.061      0.103    -10.356      0.000
    X2                 2.057      0.192     10.710      0.000

 Intercepts
    Y1                 0.955      0.033     29.106      0.000
    Y2                 1.981      0.024     82.469      0.000

 Thresholds
    U1$1              -0.078      0.243     -0.322      0.748

 Residual Variances
    Y1                 0.526      0.035     14.881      0.000
    Y2                 0.280      0.019     14.400      0.000


R-SQUARE

    Observed                   Residual
    Variable        Estimate   Variance

    Y1                 0.268
    Y2                 0.341
    U1                 0.974      0.145


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.262E-02
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  14:38:05
        Ending Time:  14:38:05
       Elapsed Time:  00:00:00



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