Mplus VERSION 7.3
MUTHEN & MUTHEN
09/22/2014   5:18 PM

INPUT INSTRUCTIONS

  title: this is an example of a Monte Carlo simulation of
          Cox mixture regression

  montecarlo: names are t u1-u5 x;
              generate=t(s 10*1) u1-u5(1);
              hazardc = t (1);
              survival=t(all);
              categorical=u1-u5;
              nobs=1000;
              class=c(2);
              genclass=c(2);
              nrep=1;
              save = ex8.17.dat;

  model population:
  %overall%
  x*1;
  t on x*0.3;
  c#1 on x*1.0;

  %c#1%
  [t#1-t#11*1];
  [u1$1-u5$1*1];
  t on x*0.3;

  %c#2%
  [t#1-t#11*0.5];
  [u1$1-u5$1*-1];
  t on x*0.8;

  analysis: type=mixture;

  model:
  %overall%
  t on x*0.3;
  c#1 on x*1.0;

  %c#1%
  [u1$1-u5$1*1];
  t on x*0.3;

  %c#2%
  [u1$1-u5$1*-1];
  t on x*0.8;

  output: tech8;



INPUT READING TERMINATED NORMALLY



this is an example of a Monte Carlo simulation of
Cox mixture regression

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        1000

Number of replications
    Requested                                                    1
    Completed                                                    1
Value of seed                                                    0

Number of dependent variables                                    6
Number of independent variables                                  1
Number of continuous latent variables                            0
Number of categorical latent variables                           1

Observed dependent variables

  Binary and ordered categorical (ordinal)
   U1          U2          U3          U4          U5

  Time-to-event (survival)

    Non-parametric
     T

Observed independent variables
   X

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
Optimization algorithm                                         EMA
Link                                                         LOGIT
Base Hazard                                   EQUAL ACROSS CLASSES


SAMPLE STATISTICS FOR THE FIRST REPLICATION


     SAMPLE STATISTICS


           Means
              X
              ________
 1             -0.001


           Covariances
              X
              ________
 X              0.996


           Correlations
              X
              ________
 X              1.000




MODEL FIT INFORMATION

Number of Free Parameters                       15

Loglikelihood

    H0 Value

        Mean                             -3025.790
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000        -3025.790      -3025.790
           0.980       0.000        -3025.790      -3025.790
           0.950       0.000        -3025.790      -3025.790
           0.900       0.000        -3025.790      -3025.790
           0.800       0.000        -3025.790      -3025.790
           0.700       0.000        -3025.790      -3025.790
           0.500       0.000        -3025.790      -3025.790
           0.300       0.000        -3025.790      -3025.790
           0.200       0.000        -3025.790      -3025.790
           0.100       0.000        -3025.790      -3025.790
           0.050       0.000        -3025.790      -3025.790
           0.020       0.000        -3025.790      -3025.790
           0.010       0.000        -3025.790      -3025.790

Information Criteria

    Akaike (AIC)

        Mean                              6081.579
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         6081.579       6081.579
           0.980       0.000         6081.579       6081.579
           0.950       0.000         6081.579       6081.579
           0.900       0.000         6081.579       6081.579
           0.800       0.000         6081.579       6081.579
           0.700       0.000         6081.579       6081.579
           0.500       0.000         6081.579       6081.579
           0.300       0.000         6081.579       6081.579
           0.200       0.000         6081.579       6081.579
           0.100       0.000         6081.579       6081.579
           0.050       0.000         6081.579       6081.579
           0.020       0.000         6081.579       6081.579
           0.010       0.000         6081.579       6081.579

    Bayesian (BIC)

        Mean                              6155.195
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         6155.195       6155.195
           0.980       0.000         6155.195       6155.195
           0.950       0.000         6155.195       6155.195
           0.900       0.000         6155.195       6155.195
           0.800       0.000         6155.195       6155.195
           0.700       0.000         6155.195       6155.195
           0.500       0.000         6155.195       6155.195
           0.300       0.000         6155.195       6155.195
           0.200       0.000         6155.195       6155.195
           0.100       0.000         6155.195       6155.195
           0.050       0.000         6155.195       6155.195
           0.020       0.000         6155.195       6155.195
           0.010       0.000         6155.195       6155.195

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

        Mean                              6107.555
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         6107.555       6107.555
           0.980       0.000         6107.555       6107.555
           0.950       0.000         6107.555       6107.555
           0.900       0.000         6107.555       6107.555
           0.800       0.000         6107.555       6107.555
           0.700       0.000         6107.555       6107.555
           0.500       0.000         6107.555       6107.555
           0.300       0.000         6107.555       6107.555
           0.200       0.000         6107.555       6107.555
           0.100       0.000         6107.555       6107.555
           0.050       0.000         6107.555       6107.555
           0.020       0.000         6107.555       6107.555
           0.010       0.000         6107.555       6107.555

Chi-Square Test of Model Fit for the Binary and Ordered Categorical
(Ordinal) Outcomes

    Pearson Chi-Square

        Mean                                22.661
        Std Dev                              0.000
        Degrees of freedom                      20
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       1.000            8.260         22.661
           0.980       1.000            9.237         22.661
           0.950       1.000           10.851         22.661
           0.900       1.000           12.443         22.661
           0.800       1.000           14.578         22.661
           0.700       1.000           16.266         22.661
           0.500       1.000           19.337         22.661
           0.300       0.000           22.775         22.661
           0.200       0.000           25.038         22.661
           0.100       0.000           28.412         22.661
           0.050       0.000           31.410         22.661
           0.020       0.000           35.020         22.661
           0.010       0.000           37.566         22.661

    Likelihood Ratio Chi-Square

        Mean                                22.148
        Std Dev                              0.000
        Degrees of freedom                      20
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       1.000            8.260         22.148
           0.980       1.000            9.237         22.148
           0.950       1.000           10.851         22.148
           0.900       1.000           12.443         22.148
           0.800       1.000           14.578         22.148
           0.700       1.000           16.266         22.148
           0.500       1.000           19.337         22.148
           0.300       0.000           22.775         22.148
           0.200       0.000           25.038         22.148
           0.100       0.000           28.412         22.148
           0.050       0.000           31.410         22.148
           0.020       0.000           35.020         22.148
           0.010       0.000           37.566         22.148



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

    Latent
   Classes

       1        494.25353          0.49425
       2        505.74647          0.50575


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

    Latent
   Classes

       1        494.25355          0.49425
       2        505.74645          0.50575


FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP

Class Counts and Proportions

    Latent
   Classes

       1              497          0.49700
       2              503          0.50300


CLASSIFICATION QUALITY

     Entropy                         0.647


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

           1        2

    1   0.895    0.105
    2   0.099    0.901


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

           1        2

    1   0.900    0.100
    2   0.104    0.896


Logits for the Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)

              1        2

    1      2.192    0.000
    2     -2.158    0.000


MODEL RESULTS

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

 T        ON
  X                   0.300     0.4018     0.0000     0.0772     0.0104 1.000 1.000

 Intercepts
  T                   0.000     0.7927     0.0000     0.1468     0.6283 0.000 1.000

 Thresholds
  U1$1                1.000     0.9291     0.0000     0.1257     0.0050 1.000 1.000
  U2$1                1.000     1.0646     0.0000     0.1285     0.0042 1.000 1.000
  U3$1                1.000     1.0441     0.0000     0.1240     0.0019 1.000 1.000
  U4$1                1.000     1.1333     0.0000     0.1332     0.0178 1.000 1.000
  U5$1                1.000     1.0796     0.0000     0.1278     0.0063 1.000 1.000

Latent Class 2

 T        ON
  X                   0.800     0.6621     0.0000     0.1100     0.0190 1.000 1.000

 Intercepts
  T                   0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000

 Thresholds
  U1$1               -1.000    -0.9735     0.0000     0.1170     0.0007 1.000 1.000
  U2$1               -1.000    -1.0770     0.0000     0.1302     0.0059 1.000 1.000
  U3$1               -1.000    -1.0777     0.0000     0.1305     0.0060 1.000 1.000
  U4$1               -1.000    -0.9591     0.0000     0.1223     0.0017 1.000 1.000
  U5$1               -1.000    -0.8914     0.0000     0.1193     0.0118 1.000 1.000

Categorical Latent Variables

 C#1        ON
  X                   1.000     1.1296     0.0000     0.1124     0.0168 1.000 1.000

 Intercepts
  C#1                 0.000    -0.0245     0.0000     0.1193     0.0006 1.000 0.000


QUALITY OF NUMERICAL RESULTS

     Average Condition Number for the Information Matrix      0.998E-01
       (ratio of smallest to largest eigenvalue)


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION FOR LATENT CLASS 1


           NU
              X
              ________
 1                  0


           LAMBDA
              X
              ________
 X                  0


           THETA
              X
              ________
 X                  0


           ALPHA
              X
              ________
 1                  0


           BETA
              X
              ________
 X                  0


           PSI
              X
              ________
 X                  0


     PARAMETER SPECIFICATION FOR LATENT CLASS 2


           NU
              X
              ________
 1                  0


           LAMBDA
              X
              ________
 X                  0


           THETA
              X
              ________
 X                  0


           ALPHA
              X
              ________
 1                  0


           BETA
              X
              ________
 X                  0


           PSI
              X
              ________
 X                  0


     PARAMETER SPECIFICATION FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS 1
              U1$1          U2$1          U3$1          U4$1          U5$1
              ________      ________      ________      ________      ________
 1                  1             2             3             4             5


           TAU(U) FOR LATENT CLASS 2
              U1$1          U2$1          U3$1          U4$1          U5$1
              ________      ________      ________      ________      ________
 1                  6             7             8             9            10


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2
              ________      ________
 1                 11             0


           GAMMA(C)
              X
              ________
 C#1               12
 C#2                0


     PARAMETER SPECIFICATION FOR THE CENSORED/NOMINAL/COUNT MODEL PART


           NU(P) FOR LATENT CLASS 1
              T#1           T
              ________      ________
 1                  0            13


           KAPPA(P) FOR LATENT CLASS 1
              X
              ________
 T#1                0
 T                 14


           NU(P) FOR LATENT CLASS 2
              T#1           T
              ________      ________
 1                  0             0


           KAPPA(P) FOR LATENT CLASS 2
              X
              ________
 T#1                0
 T                 15


     STARTING VALUES FOR LATENT CLASS 1


           NU
              X
              ________
 1              0.000


           LAMBDA
              X
              ________
 X              1.000


           THETA
              X
              ________
 X              0.000


           ALPHA
              X
              ________
 1              0.000


           BETA
              X
              ________
 X              0.000


           PSI
              X
              ________
 X              0.500


     STARTING VALUES FOR LATENT CLASS 2


           NU
              X
              ________
 1              0.000


           LAMBDA
              X
              ________
 X              1.000


           THETA
              X
              ________
 X              0.000


           ALPHA
              X
              ________
 1              0.000


           BETA
              X
              ________
 X              0.000


           PSI
              X
              ________
 X              0.500


     STARTING VALUES FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS 1
              U1$1          U2$1          U3$1          U4$1          U5$1
              ________      ________      ________      ________      ________
 1              1.000         1.000         1.000         1.000         1.000


           TAU(U) FOR LATENT CLASS 2
              U1$1          U2$1          U3$1          U4$1          U5$1
              ________      ________      ________      ________      ________
 1             -1.000        -1.000        -1.000        -1.000        -1.000


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


           GAMMA(C)
              X
              ________
 C#1            1.000
 C#2            0.000


     STARTING VALUES FOR THE CENSORED/NOMINAL/COUNT MODEL PART


           NU(P) FOR LATENT CLASS 1
              T#1           T
              ________      ________
 1            -20.000         0.000


           KAPPA(P) FOR LATENT CLASS 1
              X
              ________
 T#1            0.000
 T              0.300


           NU(P) FOR LATENT CLASS 2
              T#1           T
              ________      ________
 1            -20.000         0.000


           KAPPA(P) FOR LATENT CLASS 2
              X
              ________
 T#1            0.000
 T              0.800


     POPULATION VALUES FOR LATENT CLASS 1


           NU
              X
              ________
 1              0.000


           LAMBDA
              X
              ________
 X              1.000


           THETA
              X
              ________
 X              0.000


           ALPHA
              X
              ________
 1              0.000


           BETA
              X
              ________
 X              0.000


           PSI
              X
              ________
 X              1.000


     POPULATION VALUES FOR LATENT CLASS 2


           NU
              X
              ________
 1              0.000


           LAMBDA
              X
              ________
 X              1.000


           THETA
              X
              ________
 X              0.000


           ALPHA
              X
              ________
 1              0.000


           BETA
              X
              ________
 X              0.000


           PSI
              X
              ________
 X              1.000


     POPULATION VALUES FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS 1
              U1$1          U2$1          U3$1          U4$1          U5$1
              ________      ________      ________      ________      ________
 1              1.000         1.000         1.000         1.000         1.000


           TAU(U) FOR LATENT CLASS 2
              U1$1          U2$1          U3$1          U4$1          U5$1
              ________      ________      ________      ________      ________
 1             -1.000        -1.000        -1.000        -1.000        -1.000


     POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


           GAMMA(C)
              X
              ________
 C#1            1.000
 C#2            0.000


     POPULATION VALUES FOR THE CENSORED/NOMINAL/COUNT MODEL PART


           NU(P) FOR LATENT CLASS 1
              T#1           T
              ________      ________
 1            -20.000         0.000


           KAPPA(P) FOR LATENT CLASS 1
              X
              ________
 T#1            0.000
 T              0.300


           NU(P) FOR LATENT CLASS 2
              T#1           T
              ________      ________
 1            -20.000         0.000


           KAPPA(P) FOR LATENT CLASS 2
              X
              ________
 T#1            0.000
 T              0.800


     POPULATION VALUES FOR THE BASE HAZARD PARAMETERS


           BASE HAZARD PARAMETERS FOR LATENT CLASS 1
              T#1           T#2           T#3           T#4           T#5
              ________      ________      ________      ________      ________
 1              1.000         1.000         1.000         1.000         1.000


           BASE HAZARD PARAMETERS FOR LATENT CLASS 1
              T#6           T#7           T#8           T#9           T#10
              ________      ________      ________      ________      ________
 1              1.000         1.000         1.000         1.000         1.000


           BASE HAZARD PARAMETERS FOR LATENT CLASS 1
              T#11
              ________
 1              1.000


           BASE HAZARD PARAMETERS FOR LATENT CLASS 2
              T#1           T#2           T#3           T#4           T#5
              ________      ________      ________      ________      ________
 1              0.500         0.500         0.500         0.500         0.500


           BASE HAZARD PARAMETERS FOR LATENT CLASS 2
              T#6           T#7           T#8           T#9           T#10
              ________      ________      ________      ________      ________
 1              0.500         0.500         0.500         0.500         0.500


           BASE HAZARD PARAMETERS FOR LATENT CLASS 2
              T#11
              ________
 1              0.500


TECHNICAL 8 OUTPUT


  TECHNICAL 8 OUTPUT FOR REPLICATION 1


  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE      CLASS COUNTS    ALGORITHM
     1 -0.30567642D+04    0.0000000    0.0000000    500.875   499.125    EM
     2 -0.30291468D+04   27.6173795    0.0090348    500.206   499.794    EM
     3 -0.30263359D+04    2.8109081    0.0009280    499.295   500.705    EM
     4 -0.30259087D+04    0.4271786    0.0001412    498.488   501.512    EM
     5 -0.30258273D+04    0.0814716    0.0000269    497.791   502.209    EM
     6 -0.30258065D+04    0.0207237    0.0000068    497.197   502.803    EM
     7 -0.30257992D+04    0.0073266    0.0000024    496.696   503.304    EM
     8 -0.30257957D+04    0.0035168    0.0000012    496.277   503.723    EM
     9 -0.30257936D+04    0.0020606    0.0000007    495.928   504.072    EM
    10 -0.30257923D+04    0.0013272    0.0000004    495.639   504.361    EM
    11 -0.30257914D+04    0.0008876    0.0000003    495.399   504.601    EM
    12 -0.30257908D+04    0.0006018    0.0000002    495.201   504.799    EM
    13 -0.30257904D+04    0.0004101    0.0000001    495.037   504.963    EM
    14 -0.30257901D+04    0.0002799    0.0000001    494.901   505.099    EM
    15 -0.30257899D+04    0.0001912    0.0000001    494.789   505.211    EM
    16 -0.30257898D+04    0.0001306    0.0000000    494.696   505.304    EM
    17 -0.30257897D+04    0.0000893    0.0000000    494.619   505.381    EM
    18 -0.30257897D+04    0.0000610    0.0000000    494.556   505.444    EM
    19 -0.30257896D+04    0.0000417    0.0000000    494.503   505.497    EM
    20 -0.30257896D+04    0.0000285    0.0000000    494.460   505.540    EM
    21 -0.30257896D+04    0.0000195    0.0000000    494.424   505.576    EM
    22 -0.30257896D+04    0.0000133    0.0000000    494.394   505.606    EM
    23 -0.30257895D+04    0.0000091    0.0000000    494.370   505.630    EM
    24 -0.30257895D+04    0.0000062    0.0000000    494.350   505.650    EM
    25 -0.30257895D+04    0.0000042    0.0000000    494.333   505.667    EM
    26 -0.30257895D+04    0.0000029    0.0000000    494.319   505.681    EM
    27 -0.30257895D+04    0.0000020    0.0000000    494.308   505.692    EM
    28 -0.30257895D+04    0.0000014    0.0000000    494.298   505.702    EM
    29 -0.30257895D+04    0.0000009    0.0000000    494.290   505.710    EM
    30 -0.30257895D+04    0.0000006    0.0000000    494.284   505.716    EM
    31 -0.30257895D+04    0.0000004    0.0000000    494.279   505.721    EM
    32 -0.30257895D+04    0.0000003    0.0000000    494.274   505.726    EM
    33 -0.30257895D+04    0.0000002    0.0000000    494.271   505.729    EM
    34 -0.30257895D+04    0.0000001    0.0000000    494.268   505.732    EM
    35 -0.30257895D+04    0.0000001    0.0000000    494.265   505.735    EM
    36 -0.30257895D+04    0.0000001    0.0000000    494.263   505.737    EM
    37 -0.30257895D+04    0.0000000    0.0000000    494.261   505.739    EM
    38 -0.30257895D+04    0.0000000    0.0000000    494.260   505.740    EM
    39 -0.30257895D+04    0.0000000    0.0000000    494.259   505.741    EM
    40 -0.30257895D+04    0.0000000    0.0000000    494.254   505.746    FS


SAVEDATA INFORMATION

  Order of variables

    T
    U1
    U2
    U3
    U4
    U5
    X
    _TCENT
    C

  Save file
    ex8.17.dat

  Save file format           Free
  Save file record length    10000


     Beginning Time:  17:18:59
        Ending Time:  17:18:59
       Elapsed Time:  00:00:00



MUTHEN & MUTHEN
3463 Stoner Ave.
Los Angeles, CA  90066

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