Mplus VERSION 8
MUTHEN & MUTHEN
04/10/2017   4:39 AM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a path analysis
  	with a categorical dependent variable and
  	a continuous mediating variable with
  	missing data
  DATA:	FILE IS ex3.17.dat;
  VARIABLE:	NAMES ARE u y x;
  	CATEGORICAL IS u;
  	MISSING IS y (999);
  ANALYSIS:ESTIMATOR = MLR;
  	INTEGRATION = MONTECARLO;
  MODEL:	y ON x;	
  	u ON y x;
  OUTPUT:	TECH1 TECH8;



INPUT READING TERMINATED NORMALLY



this is an example of a path analysis
with a categorical dependent variable and
a continuous mediating variable with
missing data

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                         500

Number of dependent variables                                    2
Number of independent variables                                  1
Number of continuous latent variables                            0

Observed dependent variables

  Continuous
   Y

  Binary and ordered categorical (ordinal)
   U

Observed independent variables
   X


Estimator                                                      MLR
Information matrix                                        OBSERVED
Optimization Specifications for the Quasi-Newton Algorithm for
Continuous Outcomes
  Maximum number of iterations                                 100
  Convergence criterion                                  0.100D-05
Optimization Specifications for the EM Algorithm
  Maximum number of iterations                                 500
  Convergence criteria
    Loglikelihood change                                 0.100D-02
    Relative loglikelihood change                        0.100D-05
    Derivative                                           0.100D-02
Optimization Specifications for the M step of the EM Algorithm for
Categorical Latent variables
  Number of M step iterations                                    1
  M step convergence criterion                           0.100D-02
  Basis for M step termination                           ITERATION
Optimization Specifications for the M step of the EM Algorithm for
Censored, Binary or Ordered Categorical (Ordinal), Unordered
Categorical (Nominal) and Count Outcomes
  Number of M step iterations                                    1
  M step convergence criterion                           0.100D-02
  Basis for M step termination                           ITERATION
  Maximum value for logit thresholds                            15
  Minimum value for logit thresholds                           -15
  Minimum expected cell size for chi-square              0.100D-01
Maximum number of iterations for H1                           2000
Convergence criterion for H1                             0.100D-03
Optimization algorithm                                         EMA
Integration Specifications
  Type                                                  MONTECARLO
  Number of integration points                                 250
  Dimensions of numerical integration                            1
  Adaptive quadrature                                           ON
  Monte Carlo integration seed                                   0
Link                                                         LOGIT
Cholesky                                                       OFF

Input data file(s)
  ex3.17.dat
Input data format  FREE


SUMMARY OF DATA

     Number of missing data patterns             2
     Number of y missing data patterns           2
     Number of u missing data patterns           1


COVARIANCE COVERAGE OF DATA

Minimum covariance coverage value   0.100


     PROPORTION OF DATA PRESENT FOR Y


           Covariance Coverage
              Y             X
              ________      ________
 Y              0.698
 X              0.698         1.000


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U
      Category 1    0.470          235.000
      Category 2    0.530          265.000



UNIVARIATE SAMPLE STATISTICS


     UNIVARIATE HIGHER-ORDER MOMENT DESCRIPTIVE STATISTICS

         Variable/         Mean/     Skewness/   Minimum/ % with                Percentiles
        Sample Size      Variance    Kurtosis    Maximum  Min/Max      20%/60%    40%/80%    Median

     Y                     0.820       0.072      -3.129    0.29%      -0.374      0.459      0.826
             349.000       1.930       0.111       5.091    0.29%       1.106      1.956
     X                    -0.067      -0.060      -3.145    0.20%      -0.870     -0.304     -0.034
             500.000       0.960       0.073       2.857    0.20%       0.205      0.741


THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                        6

Loglikelihood

          H0 Value                        -820.920
          H0 Scaling Correction Factor      1.0277
            for MLR

Information Criteria

          Akaike (AIC)                    1653.839
          Bayesian (BIC)                  1679.127
          Sample-Size Adjusted BIC        1660.083
            (n* = (n + 2) / 24)



MODEL RESULTS

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

 Y          ON
    X                 -1.006      0.060    -16.894      0.000

 U          ON
    Y                  0.489      0.123      3.974      0.000
    X                  1.027      0.171      5.993      0.000

 Intercepts
    Y                  0.537      0.056      9.677      0.000

 Thresholds
    U$1                0.093      0.117      0.796      0.426

 Residual Variances
    Y                  1.019      0.077     13.234      0.000


LOGISTIC REGRESSION ODDS RATIO RESULTS

 U          ON
    Y                  1.630
    X                  2.792


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.492E-01
       (ratio of smallest to largest eigenvalue)


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION


           TAU
              U$1
              ________
                    6


           NU
              U             Y             X
              ________      ________      ________
                    0             0             0


           LAMBDA
              U             Y             X
              ________      ________      ________
 U                  0             0             0
 Y                  0             0             0
 X                  0             0             0


           THETA
              U             Y             X
              ________      ________      ________
 U                  0
 Y                  0             0
 X                  0             0             0


           ALPHA
              U             Y             X
              ________      ________      ________
                    0             1             0


           BETA
              U             Y             X
              ________      ________      ________
 U                  0             2             3
 Y                  0             0             4
 X                  0             0             0


           PSI
              U             Y             X
              ________      ________      ________
 U                  0
 Y                  0             5
 X                  0             0             0


     STARTING VALUES


           TAU
              U$1
              ________
               -0.120


           NU
              U             Y             X
              ________      ________      ________
                0.000         0.000         0.000


           LAMBDA
              U             Y             X
              ________      ________      ________
 U              1.000         0.000         0.000
 Y              0.000         1.000         0.000
 X              0.000         0.000         1.000


           THETA
              U             Y             X
              ________      ________      ________
 U              0.000
 Y              0.000         0.000
 X              0.000         0.000         0.000


           ALPHA
              U             Y             X
              ________      ________      ________
                0.000         0.820         0.000


           BETA
              U             Y             X
              ________      ________      ________
 U              0.000         0.000         0.000
 Y              0.000         0.000         0.000
 X              0.000         0.000         0.000


           PSI
              U             Y             X
              ________      ________      ________
 U              1.000
 Y              0.000         0.965
 X              0.000         0.000         0.480


TECHNICAL 8 OUTPUT


   E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
              1 -0.10091903D+04    0.0000000    0.0000000  EM
              2 -0.84555613D+03  163.6341494    0.1621440  EM
              3 -0.82681722D+03   18.7389086    0.0221616  EM
              4 -0.82226690D+03    4.5503226    0.0055034  EM
              5 -0.82123578D+03    1.0311165    0.0012540  EM
              6 -0.82100270D+03    0.2330777    0.0002838  EM
              7 -0.82094508D+03    0.0576210    0.0000702  EM
              8 -0.82092860D+03    0.0164822    0.0000201  EM
              9 -0.82092306D+03    0.0055363    0.0000067  EM
             10 -0.82092094D+03    0.0021243    0.0000026  EM
             11 -0.82092005D+03    0.0008895    0.0000011  EM
             12 -0.82091966D+03    0.0003909    0.0000005  EM


     Beginning Time:  04:39:38
        Ending Time:  04:39:38
       Elapsed Time:  00:00:00



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