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

INPUT INSTRUCTIONS

  TITLE:   this is an example of a LCGA for a three-
  	category outcome

  montecarlo:
  	names are u1-u4;
  	generate = u1-u4(2);
  	categorical = u1-u4;
  	genclasses = c(2);
  	classes = c(2);
  	nobs = 500;
  	seed = 3454367;
  	nrep = 1;
  	save = ex8.10.dat;

  ANALYSIS:
  	TYPE = MIXTURE;

  model population:
  	%overall%
  	i s | u1@0 u2@1 u3@2 u4@3;
  	[i*1 s*1];

  	[u1$1-u4$1*1];
  	[u1$2-u4$2*1.5];

  	%c#2%

  	[i@0 s*0];

  MODEL:
      %overall%
  	i s | u1@0 u2@1 u3@2 u4@3;
  	[i*1 s*1];

  	[u1$1-u4$1*1] (1);
  	[u1$2-u4$2*1.5] (2);

  	%c#2%

  	[i@0 s*0];


  OUTPUT:
  	tech8 tech9;



INPUT READING TERMINATED NORMALLY



this is an example of a LCGA for a three-
category outcome

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                         500

Number of replications
    Requested                                                    1
    Completed                                                    1
Value of seed                                              3454367

Number of dependent variables                                    4
Number of independent variables                                  0
Number of continuous latent variables                            2
Number of categorical latent variables                           1

Observed dependent variables

  Binary and ordered categorical (ordinal)
   U1          U2          U3          U4

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
Optimization algorithm                                         EMA
Link                                                         LOGIT





MODEL FIT INFORMATION

Number of Free Parameters                        6

Loglikelihood

    H0 Value

        Mean                             -1706.048
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000        -1706.048      -1706.048
           0.980       0.000        -1706.048      -1706.048
           0.950       0.000        -1706.048      -1706.048
           0.900       0.000        -1706.048      -1706.048
           0.800       0.000        -1706.048      -1706.048
           0.700       0.000        -1706.048      -1706.048
           0.500       0.000        -1706.048      -1706.048
           0.300       0.000        -1706.048      -1706.048
           0.200       0.000        -1706.048      -1706.048
           0.100       0.000        -1706.048      -1706.048
           0.050       0.000        -1706.048      -1706.048
           0.020       0.000        -1706.048      -1706.048
           0.010       0.000        -1706.048      -1706.048

Information Criteria

    Akaike (AIC)

        Mean                              3424.096
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         3424.096       3424.096
           0.980       0.000         3424.096       3424.096
           0.950       0.000         3424.096       3424.096
           0.900       0.000         3424.096       3424.096
           0.800       0.000         3424.096       3424.096
           0.700       0.000         3424.096       3424.096
           0.500       0.000         3424.096       3424.096
           0.300       0.000         3424.096       3424.096
           0.200       0.000         3424.096       3424.096
           0.100       0.000         3424.096       3424.096
           0.050       0.000         3424.096       3424.096
           0.020       0.000         3424.096       3424.096
           0.010       0.000         3424.096       3424.096

    Bayesian (BIC)

        Mean                              3449.384
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         3449.384       3449.384
           0.980       0.000         3449.384       3449.384
           0.950       0.000         3449.384       3449.384
           0.900       0.000         3449.384       3449.384
           0.800       0.000         3449.384       3449.384
           0.700       0.000         3449.384       3449.384
           0.500       0.000         3449.384       3449.384
           0.300       0.000         3449.384       3449.384
           0.200       0.000         3449.384       3449.384
           0.100       0.000         3449.384       3449.384
           0.050       0.000         3449.384       3449.384
           0.020       0.000         3449.384       3449.384
           0.010       0.000         3449.384       3449.384

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

        Mean                              3430.339
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         3430.339       3430.339
           0.980       0.000         3430.339       3430.339
           0.950       0.000         3430.339       3430.339
           0.900       0.000         3430.339       3430.339
           0.800       0.000         3430.339       3430.339
           0.700       0.000         3430.339       3430.339
           0.500       0.000         3430.339       3430.339
           0.300       0.000         3430.339       3430.339
           0.200       0.000         3430.339       3430.339
           0.100       0.000         3430.339       3430.339
           0.050       0.000         3430.339       3430.339
           0.020       0.000         3430.339       3430.339
           0.010       0.000         3430.339       3430.339

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

    Pearson Chi-Square

        Mean                                69.894
        Std Dev                              0.000
        Degrees of freedom                      74
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       1.000           48.666         69.894
           0.980       1.000           51.208         69.894
           0.950       1.000           55.189         69.894
           0.900       1.000           58.900         69.894
           0.800       1.000           63.616         69.894
           0.700       1.000           67.170         69.894
           0.500       0.000           73.334         69.894
           0.300       0.000           79.865         69.894
           0.200       0.000           83.997         69.894
           0.100       0.000           89.956         69.894
           0.050       0.000           95.081         69.894
           0.020       0.000          101.074         69.894
           0.010       0.000          105.202         69.894

    Likelihood Ratio Chi-Square

        Mean                                74.075
        Std Dev                              0.000
        Degrees of freedom                      74
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       1.000           48.666         74.075
           0.980       1.000           51.208         74.075
           0.950       1.000           55.189         74.075
           0.900       1.000           58.900         74.075
           0.800       1.000           63.616         74.075
           0.700       1.000           67.170         74.075
           0.500       1.000           73.334         74.075
           0.300       0.000           79.865         74.075
           0.200       0.000           83.997         74.075
           0.100       0.000           89.956         74.075
           0.050       0.000           95.081         74.075
           0.020       0.000          101.074         74.075
           0.010       0.000          105.202         74.075



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

    Latent
   Classes

       1        240.72044          0.48144
       2        259.27956          0.51856


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

    Latent
   Classes

       1        240.72044          0.48144
       2        259.27956          0.51856


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

Class Counts and Proportions

    Latent
   Classes

       1              244          0.48800
       2              256          0.51200


CLASSIFICATION QUALITY

     Entropy                         0.705


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

           1        2

    1   0.913    0.087
    2   0.070    0.930


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

           1        2

    1   0.925    0.075
    2   0.082    0.918


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

              1        2

    1      2.516    0.000
    2     -2.415    0.000


MODEL RESULTS

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

 I        |
  U1                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  U2                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  U3                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  U4                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000

 S        |
  U1                  0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  U2                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  U3                  2.000     2.0000     0.0000     0.0000     0.0000 1.000 0.000
  U4                  3.000     3.0000     0.0000     0.0000     0.0000 1.000 0.000

 Means
  I                   1.000     0.7172     0.0000     0.1793     0.0800 1.000 1.000
  S                   1.000     1.0696     0.0000     0.1140     0.0048 1.000 1.000

 Thresholds
  U1$1                1.000     0.7461     0.0000     0.1180     0.0645 0.000 1.000
  U1$2                1.500     1.2762     0.0000     0.1184     0.0501 1.000 1.000
  U2$1                1.000     0.7461     0.0000     0.1180     0.0645 0.000 1.000
  U2$2                1.500     1.2762     0.0000     0.1184     0.0501 1.000 1.000
  U3$1                1.000     0.7461     0.0000     0.1180     0.0645 0.000 1.000
  U3$2                1.500     1.2762     0.0000     0.1184     0.0501 1.000 1.000
  U4$1                1.000     0.7461     0.0000     0.1180     0.0645 0.000 1.000
  U4$2                1.500     1.2762     0.0000     0.1184     0.0501 1.000 1.000

Latent Class 2

 I        |
  U1                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  U2                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  U3                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  U4                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000

 S        |
  U1                  0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  U2                  1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  U3                  2.000     2.0000     0.0000     0.0000     0.0000 1.000 0.000
  U4                  3.000     3.0000     0.0000     0.0000     0.0000 1.000 0.000

 Means
  I                   0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  S                   0.000    -0.1175     0.0000     0.0771     0.0138 1.000 0.000

 Thresholds
  U1$1                1.000     0.7461     0.0000     0.1180     0.0645 0.000 1.000
  U1$2                1.500     1.2762     0.0000     0.1184     0.0501 1.000 1.000
  U2$1                1.000     0.7461     0.0000     0.1180     0.0645 0.000 1.000
  U2$2                1.500     1.2762     0.0000     0.1184     0.0501 1.000 1.000
  U3$1                1.000     0.7461     0.0000     0.1180     0.0645 0.000 1.000
  U3$2                1.500     1.2762     0.0000     0.1184     0.0501 1.000 1.000
  U4$1                1.000     0.7461     0.0000     0.1180     0.0645 0.000 1.000
  U4$2                1.500     1.2762     0.0000     0.1184     0.0501 1.000 1.000

Categorical Latent Variables

 Means
  C#1                 0.000    -0.0743     0.0000     0.1374     0.0055 1.000 0.000


QUALITY OF NUMERICAL RESULTS

     Average Condition Number for the Information Matrix      0.118E-01
       (ratio of smallest to largest eigenvalue)


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION FOR LATENT CLASS 1


     PARAMETER SPECIFICATION FOR LATENT CLASS 2


     PARAMETER SPECIFICATION FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS 1
              U1$1          U1$2          U2$1          U2$2          U3$1
              ________      ________      ________      ________      ________
 1                  1             2             1             2             1


           TAU(U) FOR LATENT CLASS 1
              U3$2          U4$1          U4$2
              ________      ________      ________
 1                  2             1             2


           TAU(U) FOR LATENT CLASS 2
              U1$1          U1$2          U2$1          U2$2          U3$1
              ________      ________      ________      ________      ________
 1                  1             2             1             2             1


           TAU(U) FOR LATENT CLASS 2
              U3$2          U4$1          U4$2
              ________      ________      ________
 1                  2             1             2


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2
              ________      ________
 1                  6             0


     PARAMETER SPECIFICATION FOR LATENT CLASS INDICATOR GROWTH MODEL PART


           LAMBDA(F) FOR LATENT CLASS 1
              I             S
              ________      ________
 U1                 0             0
 U2                 0             0
 U3                 0             0
 U4                 0             0


           ALPHA(F) FOR LATENT CLASS 1
              I             S
              ________      ________
 1                  3             4


           LAMBDA(F) FOR LATENT CLASS 2
              I             S
              ________      ________
 U1                 0             0
 U2                 0             0
 U3                 0             0
 U4                 0             0


           ALPHA(F) FOR LATENT CLASS 2
              I             S
              ________      ________
 1                  0             5


     STARTING VALUES FOR LATENT CLASS 1


     STARTING VALUES FOR LATENT CLASS 2


     STARTING VALUES FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS 1
              U1$1          U1$2          U2$1          U2$2          U3$1
              ________      ________      ________      ________      ________
 1              1.000         1.500         1.000         1.500         1.000


           TAU(U) FOR LATENT CLASS 1
              U3$2          U4$1          U4$2
              ________      ________      ________
 1              1.500         1.000         1.500


           TAU(U) FOR LATENT CLASS 2
              U1$1          U1$2          U2$1          U2$2          U3$1
              ________      ________      ________      ________      ________
 1              1.000         1.500         1.000         1.500         1.000


           TAU(U) FOR LATENT CLASS 2
              U3$2          U4$1          U4$2
              ________      ________      ________
 1              1.500         1.000         1.500


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


     STARTING VALUES FOR LATENT CLASS INDICATOR GROWTH MODEL PART


           LAMBDA(F) FOR CLASS LATENT CLASS 1
              I             S
              ________      ________
 U1             1.000         0.000
 U2             1.000         1.000
 U3             1.000         2.000
 U4             1.000         3.000


           ALPHA(F) FOR LATENT CLASS 1
              I             S
              ________      ________
 1              1.000         1.000


           LAMBDA(F) FOR CLASS LATENT CLASS 2
              I             S
              ________      ________
 U1             1.000         0.000
 U2             1.000         1.000
 U3             1.000         2.000
 U4             1.000         3.000


           ALPHA(F) FOR LATENT CLASS 2
              I             S
              ________      ________
 1              0.000         0.000


     POPULATION VALUES FOR LATENT CLASS 1


     POPULATION VALUES FOR LATENT CLASS 2


     POPULATION VALUES FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS 1
              U1$1          U1$2          U2$1          U2$2          U3$1
              ________      ________      ________      ________      ________
 1              1.000         1.500         1.000         1.500         1.000


           TAU(U) FOR LATENT CLASS 1
              U3$2          U4$1          U4$2
              ________      ________      ________
 1              1.500         1.000         1.500


           TAU(U) FOR LATENT CLASS 2
              U1$1          U1$2          U2$1          U2$2          U3$1
              ________      ________      ________      ________      ________
 1              1.000         1.500         1.000         1.500         1.000


           TAU(U) FOR LATENT CLASS 2
              U3$2          U4$1          U4$2
              ________      ________      ________
 1              1.500         1.000         1.500


     POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


     POPULATION VALUES FOR LATENT CLASS INDICATOR GROWTH MODEL PART


           LAMBDA(F) FOR LATENT CLASS 1
              I             S
              ________      ________
 U1             1.000         0.000
 U2             1.000         1.000
 U3             1.000         2.000
 U4             1.000         3.000


           ALPHA(F) FOR LATENT CLASS 1
              I             S
              ________      ________
 1              1.000         1.000


           LAMBDA(F) FOR LATENT CLASS 2
              I             S
              ________      ________
 U1             1.000         0.000
 U2             1.000         1.000
 U3             1.000         2.000
 U4             1.000         3.000


           ALPHA(F) FOR LATENT CLASS 2
              I             S
              ________      ________
 1              0.000         0.000


TECHNICAL 8 OUTPUT


  TECHNICAL 8 OUTPUT FOR REPLICATION 1


  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE      CLASS COUNTS    ALGORITHM
     1 -0.17086500D+04    0.0000000    0.0000000    244.884   255.116    EM
     2 -0.17062090D+04    2.4409741    0.0014286    244.218   255.782    EM
     3 -0.17060918D+04    0.1172387    0.0000687    243.681   256.319    EM
     4 -0.17060716D+04    0.0202001    0.0000118    243.182   256.818    EM
     5 -0.17060634D+04    0.0081486    0.0000048    242.754   257.246    EM
     6 -0.17060584D+04    0.0050191    0.0000029    242.396   257.604    EM
     7 -0.17060551D+04    0.0033547    0.0000020    242.100   257.900    EM
     8 -0.17060528D+04    0.0022682    0.0000013    241.856   258.144    EM
     9 -0.17060513D+04    0.0015359    0.0000009    241.655   258.345    EM
    10 -0.17060502D+04    0.0010403    0.0000006    241.490   258.510    EM
    11 -0.17060495D+04    0.0007046    0.0000004    241.354   258.646    EM
    12 -0.17060490D+04    0.0004773    0.0000003    241.242   258.758    EM
    13 -0.17060487D+04    0.0003233    0.0000002    241.149   258.851    EM
    14 -0.17060485D+04    0.0002190    0.0000001    241.074   258.926    EM
    15 -0.17060483D+04    0.0001484    0.0000001    241.011   258.989    EM
    16 -0.17060482D+04    0.0001005    0.0000001    240.960   259.040    EM
    17 -0.17060482D+04    0.0000681    0.0000000    240.917   259.083    EM
    18 -0.17060481D+04    0.0000461    0.0000000    240.882   259.118    EM
    19 -0.17060481D+04    0.0000313    0.0000000    240.854   259.146    EM
    20 -0.17060481D+04    0.0000212    0.0000000    240.830   259.170    EM
    21 -0.17060481D+04    0.0000143    0.0000000    240.811   259.189    EM
    22 -0.17060481D+04    0.0000097    0.0000000    240.795   259.205    EM
    23 -0.17060480D+04    0.0000066    0.0000000    240.782   259.218    EM
    24 -0.17060480D+04    0.0000045    0.0000000    240.771   259.229    EM
    25 -0.17060480D+04    0.0000030    0.0000000    240.762   259.238    EM
    26 -0.17060480D+04    0.0000020    0.0000000    240.754   259.246    EM
    27 -0.17060480D+04    0.0000014    0.0000000    240.748   259.252    EM
    28 -0.17060480D+04    0.0000009    0.0000000    240.743   259.257    EM
    29 -0.17060480D+04    0.0000006    0.0000000    240.739   259.261    EM
    30 -0.17060480D+04    0.0000004    0.0000000    240.736   259.264    EM
    31 -0.17060480D+04    0.0000003    0.0000000    240.733   259.267    EM
    32 -0.17060480D+04    0.0000002    0.0000000    240.731   259.269    EM
    33 -0.17060480D+04    0.0000001    0.0000000    240.729   259.271    EM
    34 -0.17060480D+04    0.0000001    0.0000000    240.727   259.273    EM
    35 -0.17060480D+04    0.0000001    0.0000000    240.726   259.274    EM
    36 -0.17060480D+04    0.0000000    0.0000000    240.725   259.275    EM
    37 -0.17060480D+04    0.0000001    0.0000000    240.720   259.280    FS


TECHNICAL 9 OUTPUT

  Error messages for each replication (if any)



SAVEDATA INFORMATION

  Order of variables

    U1
    U2
    U3
    U4
    C

  Save file
    ex8.10.dat

  Save file format           Free
  Save file record length    10000


     Beginning Time:  17:18:46
        Ending Time:  17:18:46
       Elapsed Time:  00:00:00



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