Mplus VERSION 6
MUTHEN & MUTHEN
04/25/2010  11:23 PM

INPUT INSTRUCTIONS

  TITLE: mc2a.inp


  Montecarlo:
          names are y1-y5;
          nobs = 500;
          nreps=500;
          seed=53487;
          classes = c(1);
          genclasses = c(2);
          save = mc2a.sav;

  analysis: type=mixture;
          estimator=ml;

  model montecarlo:


          %overall%



          i by y1-y5@1;
          s by y1@0 y2@1 y3@2 y4@3 y5@4;

          [i*1.5 s*1.6 y1-y5@0];

          i*1; s*.2; i with s*.11;

          y1*1.0 y2*1.42 y3*2.24 y4*3.46 y5*5.08;


          [c#1@-2];


          %c#1%

          [i*15 s*1.6];

          i*5; s*.2; i with s*.11;
          y1*1.0 y2*1.42 y3*2.24 y4*3.46 y5*5.08;


          %c#2%

          [i*0 s*0];

          i*1; s*.2; i with s*.11;
          y1*1.0 y2*1.42 y3*2.24 y4*3.46 y5*5.08;


  model:


          %overall%

          i by y1-y5@1;
          s by y1@0 y2@1 y3@2 y4@3 y5@4;

          [i s y1-y5@0];

          i*25.3642; s*0.4757; i with s*2.6744;

          y1*1.0098 y2*1.4256 y3*2.2380
           y4*3.4435 y5*5.0170;

          %c#1%

          [i*1.8161 s*0.1930];


  output:
          tech9;




INPUT READING TERMINATED NORMALLY



mc2a.inp

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                         500

Number of replications
    Requested                                                  500
    Completed                                                  500
Value of seed                                                53487

Number of dependent variables                                    5
Number of independent variables                                  0
Number of continuous latent variables                            2
Number of categorical latent variables                           1

Observed dependent variables

  Continuous
   Y1          Y2          Y3          Y4          Y5

Continuous latent variables
   I           S

Categorical latent variables
   C


Estimator                                                       ML
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-06
    Relative loglikelihood change                        0.100D-06
    Derivative                                           0.100D-05
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-05
  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-05
  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
Optimization algorithm                                         EMA


SAMPLE STATISTICS FOR THE FIRST REPLICATION


     SAMPLE STATISTICS


           Means
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 1              1.633         1.843         2.046         2.147         2.244


           Covariances
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 Y1            23.263
 Y2            24.410        28.322
 Y3            27.436        30.386        36.988
 Y4            30.113        33.626        38.675        46.259
 Y5            31.815        35.757        41.228        46.427        54.855


           Correlations
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 Y1             1.000
 Y2             0.951         1.000
 Y3             0.935         0.939         1.000
 Y4             0.918         0.929         0.935         1.000
 Y5             0.891         0.907         0.915         0.922         1.000




TESTS OF MODEL FIT

Number of Free Parameters                       10

Loglikelihood

    H0 Value

        Mean                             -5790.074
        Std Dev                             39.843
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.986        -5882.762      -5892.519
           0.980       0.976        -5871.901      -5878.378
           0.950       0.952        -5855.613      -5855.469
           0.900       0.898        -5841.138      -5842.333
           0.800       0.830        -5823.607      -5821.604
           0.700       0.708        -5810.968      -5810.246
           0.500       0.498        -5790.074      -5790.653
           0.300       0.290        -5769.181      -5771.286
           0.200       0.192        -5756.542      -5757.700
           0.100       0.110        -5739.011      -5737.881
           0.050       0.048        -5724.536      -5727.760
           0.020       0.022        -5708.248      -5706.969
           0.010       0.016        -5697.387      -5692.447

Information Criteria

    Akaike (AIC)

        Mean                             11600.149
        Std Dev                             79.687
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.984        11414.773      11401.355
           0.980       0.978        11436.496      11431.705
           0.950       0.952        11469.072      11471.618
           0.900       0.890        11498.022      11494.042
           0.800       0.808        11533.084      11534.252
           0.700       0.710        11558.361      11561.640
           0.500       0.502        11600.149      11600.505
           0.300       0.292        11641.937      11639.976
           0.200       0.170        11667.213      11662.666
           0.100       0.102        11702.275      11702.615
           0.050       0.048        11731.226      11729.335
           0.020       0.024        11763.802      11770.805
           0.010       0.014        11785.524      11797.000

    Bayesian (BIC)

        Mean                             11642.295
        Std Dev                             79.687
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.984        11456.919      11443.501
           0.980       0.978        11478.642      11473.851
           0.950       0.952        11511.218      11513.764
           0.900       0.890        11540.168      11536.189
           0.800       0.808        11575.231      11576.398
           0.700       0.710        11600.507      11603.786
           0.500       0.502        11642.295      11642.651
           0.300       0.292        11684.083      11682.122
           0.200       0.170        11709.359      11704.812
           0.100       0.102        11744.422      11744.761
           0.050       0.048        11773.372      11771.481
           0.020       0.024        11805.948      11812.951
           0.010       0.014        11827.670      11839.146

    Sample-Size Adjusted BIC (n* = (n + 2) / 24)

        Mean                             11610.554
        Std Dev                             79.687
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.984        11425.179      11411.761
           0.980       0.978        11446.902      11442.111
           0.950       0.952        11479.477      11482.023
           0.900       0.890        11508.428      11504.448
           0.800       0.808        11543.490      11544.658
           0.700       0.710        11568.767      11572.045
           0.500       0.502        11610.554      11610.911
           0.300       0.292        11652.342      11650.382
           0.200       0.170        11677.619      11673.071
           0.100       0.102        11712.681      11713.021
           0.050       0.048        11741.631      11739.740
           0.020       0.024        11774.207      11781.211
           0.010       0.014        11795.930      11807.405



FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THE ESTIMATED MODEL

    Latent
   Classes

       1        500.00000          1.00000


FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS
BASED ON ESTIMATED POSTERIOR PROBABILITIES

    Latent
   Classes

       1        500.00000          1.00000


CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP

Class Counts and Proportions

    Latent
   Classes

       1              500          1.00000


Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)

           1

    1   1.000


MODEL RESULTS

                           ESTIMATES              S. E.     M. S. E.  95%  % Sig
              Population   Average   Std. Dev.   Average             Cover Coeff
Latent Class 1

 I        BY
  Y1               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y4               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y5               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000

 S        BY
  Y1               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               2.000     2.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y4               3.000     3.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y5               4.000     4.0000     0.0000     0.0000     0.0000 1.000 0.000

 I        WITH
  S                2.674     2.6441     0.2917     0.2207     0.0858 0.844 1.000

 Means
  I                1.816     1.8101     0.2226     0.2279     0.0495 0.944 1.000
  S                0.193     0.1934     0.0370     0.0375     0.0014 0.958 1.000

 Intercepts
  Y1               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y4               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y5               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000

 Variances
  I               25.364    25.2987     2.6449     1.6487     6.9856 0.780 1.000
  S                0.476     0.4667     0.0506     0.0472     0.0026 0.912 1.000

 Residual Variances
  Y1               1.010     1.0034     0.1444     0.1437     0.0209 0.954 1.000
  Y2               1.426     1.4199     0.1227     0.1260     0.0150 0.938 1.000
  Y3               2.238     2.2434     0.1834     0.1801     0.0336 0.944 1.000
  Y4               3.444     3.4674     0.2709     0.2833     0.0738 0.960 1.000
  Y5               5.017     5.0958     0.4491     0.4440     0.2075 0.948 1.000


QUALITY OF NUMERICAL RESULTS

     Average Condition Number for the Information Matrix      0.156E-02
       (ratio of smallest to largest eigenvalue)


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION FOR LATENT CLASS 1


           NU
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 1                  0             0             0             0             0


           LAMBDA
              I             S
              ________      ________
 Y1                 0             0
 Y2                 0             0
 Y3                 0             0
 Y4                 0             0
 Y5                 0             0


           THETA
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 Y1                 1
 Y2                 0             2
 Y3                 0             0             3
 Y4                 0             0             0             4
 Y5                 0             0             0             0             5


           ALPHA
              I             S
              ________      ________
 1                  6             7


           BETA
              I             S
              ________      ________
 I                  0             0
 S                  0             0


           PSI
              I             S
              ________      ________
 I                  8
 S                  9            10


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1
              ________
 1                  0


     STARTING VALUES FOR LATENT CLASS 1


           NU
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 1              0.000         0.000         0.000         0.000         0.000


           LAMBDA
              I             S
              ________      ________
 Y1             1.000         0.000
 Y2             1.000         1.000
 Y3             1.000         2.000
 Y4             1.000         3.000
 Y5             1.000         4.000


           THETA
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 Y1             1.010
 Y2             0.000         1.426
 Y3             0.000         0.000         2.238
 Y4             0.000         0.000         0.000         3.444
 Y5             0.000         0.000         0.000         0.000         5.017


           ALPHA
              I             S
              ________      ________
 1              1.816         0.193


           BETA
              I             S
              ________      ________
 I              0.000         0.000
 S              0.000         0.000


           PSI
              I             S
              ________      ________
 I             25.364
 S              2.674         0.476


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1
              ________
 1              0.000


     POPULATION VALUES FOR LATENT CLASS 1


           NU
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 1              0.000         0.000         0.000         0.000         0.000


           LAMBDA
              I             S
              ________      ________
 Y1             1.000         0.000
 Y2             1.000         1.000
 Y3             1.000         2.000
 Y4             1.000         3.000
 Y5             1.000         4.000


           THETA
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 Y1             1.000
 Y2             0.000         1.420
 Y3             0.000         0.000         2.240
 Y4             0.000         0.000         0.000         3.460
 Y5             0.000         0.000         0.000         0.000         5.080


           ALPHA
              I             S
              ________      ________
 1             15.000         1.600


           BETA
              I             S
              ________      ________
 I              0.000         0.000
 S              0.000         0.000


           PSI
              I             S
              ________      ________
 I              5.000
 S              0.110         0.200


     POPULATION VALUES FOR LATENT CLASS 2


           NU
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 1              0.000         0.000         0.000         0.000         0.000


           LAMBDA
              I             S
              ________      ________
 Y1             1.000         0.000
 Y2             1.000         1.000
 Y3             1.000         2.000
 Y4             1.000         3.000
 Y5             1.000         4.000


           THETA
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 Y1             1.000
 Y2             0.000         1.420
 Y3             0.000         0.000         2.240
 Y4             0.000         0.000         0.000         3.460
 Y5             0.000         0.000         0.000         0.000         5.080


           ALPHA
              I             S
              ________      ________
 1              0.000         0.000


           BETA
              I             S
              ________      ________
 I              0.000         0.000
 S              0.000         0.000


           PSI
              I             S
              ________      ________
 I              1.000
 S              0.110         0.200


     POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2
              ________      ________
 1             -2.000         0.000


TECHNICAL 9 OUTPUT

  Error messages for each replication (if any)



SAVEDATA INFORMATION

  Order of variables

    Y1
    Y2
    Y3
    Y4
    Y5
    C

  Save file
    mc2a.sav

  Save file format           Free
  Save file record length    5000


     Beginning Time:  23:23:55
        Ending Time:  23:23:59
       Elapsed Time:  00:00:04



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