Mplus VERSION 6
MUTHEN & MUTHEN
04/25/2010  11:24 PM

INPUT INSTRUCTIONS

  TITLE: mc2d.inp


  Montecarlo:
          names are y1-y5 x;
          nobs = 500;
          nreps=500;
          seed=53487;
          classes = c(1);
          genclasses = c(2);
          save = mc2d.sav;
          missing=y1-y5;

  analysis: type=mixture missing;
          estimator=mlr;

  model montecarlo:


          %overall%

                  [x@0];
                  x@1;


          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;

          i on x*.7;
                  s on x*.2;

          [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;

          i on x*.7;
                  s on x*.2;

          %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;

          i on x*.7;
                  s on x*.2;

  model missing:

          %Overall%
          [y1-y5@-1];
          y2-y5 on x@1;

  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;

          i on x*0.6926;
                  s on x*0.1988;


          %c#1%

          [i*1.8161 s*0.1930];


  output:
          tech9;




*** WARNING in ANALYSIS command
  Starting with Version 5, TYPE=MISSING is the default for all analyses.
  To obtain listwise deletion, use LISTWISE=ON in the DATA command.
   1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS



mc2d.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                                  1
Number of continuous latent variables                            2
Number of categorical latent variables                           1

Observed dependent variables

  Continuous
   Y1          Y2          Y3          Y4          Y5

Observed independent variables
   X

Continuous latent variables
   I           S

Categorical latent variables
   C


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-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
Maximum number of iterations for H1                           2000
Convergence criterion for H1                             0.100D-03
Optimization algorithm                                         EMA


SUMMARY OF DATA FOR THE FIRST REPLICATION

     Number of missing data patterns            31
     Number of y missing data patterns          31
     Number of u missing data patterns           0


SUMMARY OF MISSING DATA PATTERNS FOR THE FIRST REPLICATION


     MISSING DATA PATTERNS FOR Y (x = not missing)

           1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20
 Y1        x  x     x  x  x     x     x  x           x     x     x  x
 Y2        x     x  x  x           x                 x     x  x
 Y3        x     x     x     x  x        x  x  x  x        x  x     x
 Y4        x  x  x  x  x  x     x  x           x  x     x     x     x
 Y5        x  x     x        x  x  x     x        x        x  x  x
 X         x  x  x  x  x  x  x  x  x  x  x  x  x  x  x  x  x  x  x  x

          21 22 23 24 25 26 27 28 29 30 31
 Y1        x  x        x  x
 Y2        x  x     x     x     x  x  x  x
 Y3           x     x  x              x
 Y4                       x  x     x
 Y5        x     x  x        x  x
 X         x  x  x  x  x  x  x  x  x  x  x


     MISSING DATA PATTERN FREQUENCIES FOR Y

    Pattern   Frequency     Pattern   Frequency     Pattern   Frequency
          1          98          12           7          23           3
          2          11          13           2          24          12
          3          13          14          20          25          14
          4          29          15           8          26          11
          5          36          16           3          27           4
          6          13          17          21          28           2
          7           6          18          38          29           3
          8          30          19          15          30           5
          9          15          20          16          31           1
         10          24          21          12
         11          17          22          11


COVARIANCE COVERAGE OF DATA FOR THE FIRST REPLICATION

Minimum covariance coverage value   0.100


     PROPORTION OF DATA PRESENT FOR Y


           Covariance Coverage
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 Y1             0.732
 Y2             0.452         0.630
 Y3             0.486         0.468         0.692
 Y4             0.488         0.486         0.506         0.684
 Y5             0.466         0.454         0.484         0.490         0.666
 X              0.732         0.630         0.692         0.684         0.666


           Covariance Coverage
              X
              ________
 X              1.000


SAMPLE STATISTICS FOR THE FIRST REPLICATION


     ESTIMATED SAMPLE STATISTICS


           Means
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 1              1.482         1.703         1.809         1.958         2.335


           Means
              X
              ________
 1              0.026


           Covariances
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 Y1            24.704
 Y2            25.861        29.801
 Y3            28.593        31.694        38.124
 Y4            30.735        34.352        39.052        45.434
 Y5            34.223        38.266        43.184        47.220        56.533
 X              0.741         0.871         1.112         1.104         1.526


           Covariances
              X
              ________
 X              1.105


           Correlations
              Y1            Y2            Y3            Y4            Y5
              ________      ________      ________      ________      ________
 Y1             1.000
 Y2             0.953         1.000
 Y3             0.932         0.940         1.000
 Y4             0.917         0.934         0.938         1.000
 Y5             0.916         0.932         0.930         0.932         1.000
 X              0.142         0.152         0.171         0.156         0.193


           Correlations
              X
              ________
 X              1.000


     MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -4854.797




TESTS OF MODEL FIT

Number of Free Parameters                       12

Loglikelihood

    H0 Value

        Mean                             -4315.888
        Std Dev                             64.770
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.990        -4466.562      -4467.982
           0.980       0.978        -4448.906      -4455.817
           0.950       0.966        -4422.428      -4414.653
           0.900       0.914        -4398.897      -4397.028
           0.800       0.796        -4370.398      -4373.679
           0.700       0.688        -4349.853      -4351.847
           0.500       0.500        -4315.888      -4316.199
           0.300       0.306        -4281.923      -4280.316
           0.200       0.188        -4261.378      -4264.584
           0.100       0.100        -4232.879      -4233.939
           0.050       0.058        -4209.348      -4206.464
           0.020       0.022        -4182.870      -4181.143
           0.010       0.010        -4165.214      -4169.296

Information Criteria

    Akaike (AIC)

        Mean                              8655.776
        Std Dev                            129.540
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.990         8354.427       8352.719
           0.980       0.978         8389.740       8383.302
           0.950       0.942         8442.696       8428.512
           0.900       0.900         8489.758       8486.155
           0.800       0.812         8546.755       8551.468
           0.700       0.694         8587.845       8584.211
           0.500       0.500         8655.776       8655.187
           0.300       0.312         8723.706       8727.539
           0.200       0.204         8764.796       8766.189
           0.100       0.086         8821.794       8815.757
           0.050       0.034         8868.856       8851.222
           0.020       0.022         8921.812       8928.000
           0.010       0.010         8957.124       8948.495

    Bayesian (BIC)

        Mean                              8706.351
        Std Dev                            129.540
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.990         8405.003       8403.295
           0.980       0.978         8440.315       8433.877
           0.950       0.942         8493.271       8479.087
           0.900       0.900         8540.333       8536.730
           0.800       0.812         8597.330       8602.043
           0.700       0.694         8638.420       8634.786
           0.500       0.500         8706.351       8705.763
           0.300       0.312         8774.282       8778.114
           0.200       0.204         8815.372       8816.765
           0.100       0.086         8872.369       8866.332
           0.050       0.034         8919.431       8901.798
           0.020       0.022         8972.387       8978.576
           0.010       0.010         9007.699       8999.070

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

        Mean                              8668.262
        Std Dev                            129.540
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.990         8366.914       8365.206
           0.980       0.978         8402.227       8395.788
           0.950       0.942         8455.182       8440.998
           0.900       0.900         8502.244       8498.641
           0.800       0.812         8559.242       8563.954
           0.700       0.694         8600.332       8596.697
           0.500       0.500         8668.262       8667.674
           0.300       0.312         8736.193       8740.025
           0.200       0.204         8777.283       8778.676
           0.100       0.086         8834.280       8828.243
           0.050       0.034         8881.342       8863.709
           0.020       0.022         8934.298       8940.487
           0.010       0.010         8969.611       8960.981



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          ON
  X                0.693     0.7036     0.2361     0.2303     0.0558 0.954 0.852

 S          ON
  X                0.199     0.2028     0.0453     0.0439     0.0021 0.948 0.992

 I        WITH
  S                2.674     2.6095     0.3234     0.3194     0.1086 0.924 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
  I                1.816     1.7740     0.2296     0.2286     0.0544 0.936 1.000
  S                0.193     0.1912     0.0406     0.0423     0.0016 0.962 0.998

 Residual Variances
  Y1               1.010     1.0025     0.2122     0.1991     0.0450 0.934 1.000
  Y2               1.426     1.4271     0.1764     0.1692     0.0311 0.930 1.000
  Y3               2.238     2.2354     0.2455     0.2370     0.0601 0.934 1.000
  Y4               3.444     3.4392     0.3740     0.3640     0.1396 0.952 1.000
  Y5               5.017     5.0355     0.5753     0.5747     0.3307 0.936 1.000
  I               25.364    24.7939     2.6771     2.7324     7.4777 0.944 1.000
  S                0.476     0.4666     0.0628     0.0630     0.0040 0.932 1.000


QUALITY OF NUMERICAL RESULTS

     Average Condition Number for the Information Matrix      0.246E-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


           NU
              X
              ________
 1                  0


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


           THETA
              X
              ________
 X                  0


           ALPHA
              I             S             X
              ________      ________      ________
 1                  6             7             0


           BETA
              I             S             X
              ________      ________      ________
 I                  0             0             8
 S                  0             0             9
 X                  0             0             0


           PSI
              I             S             X
              ________      ________      ________
 I                 10
 S                 11            12
 X                  0             0             0


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1
              ________
 1                  0


           GAMMA(C)
              X
              ________
 C#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


           NU
              X
              ________
 1              0.000


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


           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
 X              0.000         0.000         0.000         0.000         0.000


           THETA
              X
              ________
 X              0.000


           ALPHA
              I             S             X
              ________      ________      ________
 1              1.816         0.193         0.000


           BETA
              I             S             X
              ________      ________      ________
 I              0.000         0.000         0.693
 S              0.000         0.000         0.199
 X              0.000         0.000         0.000


           PSI
              I             S             X
              ________      ________      ________
 I             25.364
 S              2.674         0.476
 X              0.000         0.000         0.500


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1
              ________
 1              0.000


           GAMMA(C)
              X
              ________
 C#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


           NU
              X
              ________
 1              0.000


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


           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
 X              0.000         0.000         0.000         0.000         0.000


           THETA
              X
              ________
 X              0.000


           ALPHA
              I             S             X
              ________      ________      ________
 1             15.000         1.600         0.000


           BETA
              I             S             X
              ________      ________      ________
 I              0.000         0.000         0.700
 S              0.000         0.000         0.200
 X              0.000         0.000         0.000


           PSI
              I             S             X
              ________      ________      ________
 I              5.000
 S              0.110         0.200
 X              0.000         0.000         1.000


     POPULATION VALUES FOR LATENT CLASS 2


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


           NU
              X
              ________
 1              0.000


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


           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
 X              0.000         0.000         0.000         0.000         0.000


           THETA
              X
              ________
 X              0.000


           ALPHA
              I             S             X
              ________      ________      ________
 1              0.000         0.000         0.000


           BETA
              I             S             X
              ________      ________      ________
 I              0.000         0.000         0.700
 S              0.000         0.000         0.200
 X              0.000         0.000         0.000


           PSI
              I             S             X
              ________      ________      ________
 I              1.000
 S              0.110         0.200
 X              0.000         0.000         1.000


     POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


           GAMMA(C)
              X
              ________
 C#1            0.000
 C#2            0.000


TECHNICAL 9 OUTPUT

  Error messages for each replication (if any)



SAVEDATA INFORMATION

  Order of variables

    Y1
    Y2
    Y3
    Y4
    Y5
    X
    C

  Save file
    mc2d.sav

  Save file format           Free
  Save file record length    5000
  Missing designated by 999


     Beginning Time:  23:24:09
        Ending Time:  23:24:16
       Elapsed Time:  00:00:07



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