Mplus VERSION 7.2
MUTHEN & MUTHEN
05/07/2014   2:04 PM

INPUT INSTRUCTIONS

  title:
  	this is an example of a mixture model with
  	different means for continuous outcomes

  montecarlo:
  	names are y1-y4;
  	genclasses = c(3);
  	classes = c(3);
  	nobs = 500;
  	seed = 3454367;
  	nrep = 1;
  	save = ex7.22.dat;

  analysis:
  	type = mixture;

  model population:

  	%overall%

  	[c#1*0 c#2*0];

  	y1 with y2-y4*.5;
  	y2 with y3-y4*.25;
  	y3 with y4*.10;

  	[y1-y4*0];

  	y1-y4*1;
  	
  	%c#2%
  	[y1-y4*-2];
  	
  	%c#3%
  	[y1-y4*2];


  model:

  	%overall%

  	[c#1*0 c#2*0];

  	y1 with y2-y4*.5;
  	y2 with y3-y4*.25;
  	y3 with y4*.10;

  	[y1-y4*0];

  	y1-y4*1;
  	
  	%c#2%
  	[y1-y4*-2];
  	
  	%c#3%
  	[y1-y4*2];


  output:
  	tech8 tech9;	
  	



INPUT READING TERMINATED NORMALLY




this is an example of a mixture model with
different means for continuous outcomes

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                            0
Number of categorical latent variables                           1

Observed dependent variables

  Continuous
   Y1          Y2          Y3          Y4

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


SAMPLE STATISTICS FOR THE FIRST REPLICATION


     SAMPLE STATISTICS


           Means
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1             -0.089        -0.118        -0.120        -0.123


           Covariances
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             3.643
 Y2             3.157         3.691
 Y3             3.142         2.926         3.660
 Y4             3.022         2.833         2.663         3.504


           Correlations
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.861         1.000
 Y3             0.861         0.796         1.000
 Y4             0.846         0.788         0.744         1.000




MODEL FIT INFORMATION

Number of Free Parameters                       24

Loglikelihood

    H0 Value

        Mean                             -3054.963
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000        -3054.963      -3054.963
           0.980       0.000        -3054.963      -3054.963
           0.950       0.000        -3054.963      -3054.963
           0.900       0.000        -3054.963      -3054.963
           0.800       0.000        -3054.963      -3054.963
           0.700       0.000        -3054.963      -3054.963
           0.500       0.000        -3054.963      -3054.963
           0.300       0.000        -3054.963      -3054.963
           0.200       0.000        -3054.963      -3054.963
           0.100       0.000        -3054.963      -3054.963
           0.050       0.000        -3054.963      -3054.963
           0.020       0.000        -3054.963      -3054.963
           0.010       0.000        -3054.963      -3054.963

Information Criteria

    Akaike (AIC)

        Mean                              6157.926
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         6157.926       6157.926
           0.980       0.000         6157.926       6157.926
           0.950       0.000         6157.926       6157.926
           0.900       0.000         6157.926       6157.926
           0.800       0.000         6157.926       6157.926
           0.700       0.000         6157.926       6157.926
           0.500       0.000         6157.926       6157.926
           0.300       0.000         6157.926       6157.926
           0.200       0.000         6157.926       6157.926
           0.100       0.000         6157.926       6157.926
           0.050       0.000         6157.926       6157.926
           0.020       0.000         6157.926       6157.926
           0.010       0.000         6157.926       6157.926

    Bayesian (BIC)

        Mean                              6259.077
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         6259.077       6259.077
           0.980       0.000         6259.077       6259.077
           0.950       0.000         6259.077       6259.077
           0.900       0.000         6259.077       6259.077
           0.800       0.000         6259.077       6259.077
           0.700       0.000         6259.077       6259.077
           0.500       0.000         6259.077       6259.077
           0.300       0.000         6259.077       6259.077
           0.200       0.000         6259.077       6259.077
           0.100       0.000         6259.077       6259.077
           0.050       0.000         6259.077       6259.077
           0.020       0.000         6259.077       6259.077
           0.010       0.000         6259.077       6259.077

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

        Mean                              6182.899
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         6182.899       6182.899
           0.980       0.000         6182.899       6182.899
           0.950       0.000         6182.899       6182.899
           0.900       0.000         6182.899       6182.899
           0.800       0.000         6182.899       6182.899
           0.700       0.000         6182.899       6182.899
           0.500       0.000         6182.899       6182.899
           0.300       0.000         6182.899       6182.899
           0.200       0.000         6182.899       6182.899
           0.100       0.000         6182.899       6182.899
           0.050       0.000         6182.899       6182.899
           0.020       0.000         6182.899       6182.899
           0.010       0.000         6182.899       6182.899



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

    Latent
   Classes

       1        162.30854          0.32462
       2        171.08795          0.34218
       3        166.60351          0.33321


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

    Latent
   Classes

       1        162.30850          0.32462
       2        171.08793          0.34218
       3        166.60356          0.33321


CLASSIFICATION QUALITY

     Entropy                         0.812


CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP

Class Counts and Proportions

    Latent
   Classes

       1              164          0.32800
       2              169          0.33800
       3              167          0.33400


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

           1        2        3

    1   0.869    0.084    0.047
    2   0.069    0.931    0.000
    3   0.049    0.000    0.951


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

           1        2        3

    1   0.878    0.072    0.050
    2   0.080    0.920    0.000
    3   0.047    0.000    0.953


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

              1        2        3

    1      2.858    0.356    0.000
    2     10.165   12.602    0.000
    3     -3.017  -13.339    0.000


MODEL RESULTS

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

 Y1       WITH
  Y2                  0.500     0.4415     0.0000     0.0719     0.0034 1.000 1.000
  Y3                  0.500     0.3968     0.0000     0.0621     0.0106 1.000 1.000
  Y4                  0.500     0.4756     0.0000     0.0685     0.0006 1.000 1.000

 Y2       WITH
  Y3                  0.250     0.1590     0.0000     0.0548     0.0083 1.000 1.000
  Y4                  0.250     0.2643     0.0000     0.0778     0.0002 1.000 1.000

 Y3       WITH
  Y4                  0.100     0.0646     0.0000     0.0539     0.0013 1.000 0.000

 Means
  Y1                  0.000    -0.0760     0.0000     0.1099     0.0058 1.000 0.000
  Y2                  0.000    -0.0736     0.0000     0.1113     0.0054 1.000 0.000
  Y3                  0.000    -0.2679     0.0000     0.1236     0.0718 0.000 1.000
  Y4                  0.000    -0.1241     0.0000     0.1334     0.0154 1.000 0.000

 Variances
  Y1                  1.000     0.9514     0.0000     0.0869     0.0024 1.000 1.000
  Y2                  1.000     0.9514     0.0000     0.0891     0.0024 1.000 1.000
  Y3                  1.000     0.8474     0.0000     0.0698     0.0233 0.000 1.000
  Y4                  1.000     1.0947     0.0000     0.1015     0.0090 1.000 1.000

Latent Class 2

 Y1       WITH
  Y2                  0.500     0.4415     0.0000     0.0719     0.0034 1.000 1.000
  Y3                  0.500     0.3968     0.0000     0.0621     0.0106 1.000 1.000
  Y4                  0.500     0.4756     0.0000     0.0685     0.0006 1.000 1.000

 Y2       WITH
  Y3                  0.250     0.1590     0.0000     0.0548     0.0083 1.000 1.000
  Y4                  0.250     0.2643     0.0000     0.0778     0.0002 1.000 1.000

 Y3       WITH
  Y4                  0.100     0.0646     0.0000     0.0539     0.0013 1.000 0.000

 Means
  Y1                 -2.000    -2.0653     0.0000     0.1086     0.0043 1.000 1.000
  Y2                 -2.000    -2.1260     0.0000     0.1010     0.0159 1.000 1.000
  Y3                 -2.000    -2.0593     0.0000     0.0934     0.0035 1.000 1.000
  Y4                 -2.000    -1.9865     0.0000     0.0976     0.0002 1.000 1.000

 Variances
  Y1                  1.000     0.9514     0.0000     0.0869     0.0024 1.000 1.000
  Y2                  1.000     0.9514     0.0000     0.0891     0.0024 1.000 1.000
  Y3                  1.000     0.8474     0.0000     0.0698     0.0233 0.000 1.000
  Y4                  1.000     1.0947     0.0000     0.1015     0.0090 1.000 1.000

Latent Class 3

 Y1       WITH
  Y2                  0.500     0.4415     0.0000     0.0719     0.0034 1.000 1.000
  Y3                  0.500     0.3968     0.0000     0.0621     0.0106 1.000 1.000
  Y4                  0.500     0.4756     0.0000     0.0685     0.0006 1.000 1.000

 Y2       WITH
  Y3                  0.250     0.1590     0.0000     0.0548     0.0083 1.000 1.000
  Y4                  0.250     0.2643     0.0000     0.0778     0.0002 1.000 1.000

 Y3       WITH
  Y4                  0.100     0.0646     0.0000     0.0539     0.0013 1.000 0.000

 Means
  Y1                  2.000     1.9279     0.0000     0.0903     0.0052 1.000 1.000
  Y2                  2.000     1.9018     0.0000     0.0984     0.0096 1.000 1.000
  Y3                  2.000     2.0147     0.0000     0.0766     0.0002 1.000 1.000
  Y4                  2.000     1.7915     0.0000     0.0955     0.0435 0.000 1.000

 Variances
  Y1                  1.000     0.9514     0.0000     0.0869     0.0024 1.000 1.000
  Y2                  1.000     0.9514     0.0000     0.0891     0.0024 1.000 1.000
  Y3                  1.000     0.8474     0.0000     0.0698     0.0233 0.000 1.000
  Y4                  1.000     1.0947     0.0000     0.1015     0.0090 1.000 1.000

Categorical Latent Variables

 Means
  C#1                 0.000    -0.0261     0.0000     0.1360     0.0007 1.000 0.000
  C#2                 0.000     0.0266     0.0000     0.1349     0.0007 1.000 0.000


QUALITY OF NUMERICAL RESULTS

     Average Condition Number for the Information Matrix      0.687E-02
       (ratio of smallest to largest eigenvalue)


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION FOR LATENT CLASS 1


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1                  1             2             3             4


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1                 5
 Y2                 6             7
 Y3                 8             9            10
 Y4                11            12            13            14


     PARAMETER SPECIFICATION FOR LATENT CLASS 2


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1                 15            16            17            18


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1                 5
 Y2                 6             7
 Y3                 8             9            10
 Y4                11            12            13            14


     PARAMETER SPECIFICATION FOR LATENT CLASS 3


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1                 19            20            21            22


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1                 5
 Y2                 6             7
 Y3                 8             9            10
 Y4                11            12            13            14


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2           C#3
              ________      ________      ________
 1                 23            24             0


     STARTING VALUES FOR LATENT CLASS 1


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


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.500         1.000
 Y3             0.500         0.250         1.000
 Y4             0.500         0.250         0.100         1.000


     STARTING VALUES FOR LATENT CLASS 2


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1             -2.000        -2.000        -2.000        -2.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.500         1.000
 Y3             0.500         0.250         1.000
 Y4             0.500         0.250         0.100         1.000


     STARTING VALUES FOR LATENT CLASS 3


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1              2.000         2.000         2.000         2.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.500         1.000
 Y3             0.500         0.250         1.000
 Y4             0.500         0.250         0.100         1.000


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2           C#3
              ________      ________      ________
 1              0.000         0.000         0.000


     POPULATION VALUES FOR LATENT CLASS 1


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


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.500         1.000
 Y3             0.500         0.250         1.000
 Y4             0.500         0.250         0.100         1.000


     POPULATION VALUES FOR LATENT CLASS 2


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1             -2.000        -2.000        -2.000        -2.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.500         1.000
 Y3             0.500         0.250         1.000
 Y4             0.500         0.250         0.100         1.000


     POPULATION VALUES FOR LATENT CLASS 3


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1              2.000         2.000         2.000         2.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.500         1.000
 Y3             0.500         0.250         1.000
 Y4             0.500         0.250         0.100         1.000


     POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2           C#3
              ________      ________      ________
 1              0.000         0.000         0.000


TECHNICAL 8 OUTPUT


  TECHNICAL 8 OUTPUT FOR REPLICATION 1


  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE      CLASS COUNTS    ALGORITHM
     1 -0.30652569D+04    0.0000000    0.0000000    164.441   179.796    EM
                                                    155.763
     2 -0.30572773D+04    7.9796746    0.0026033    161.858   179.495    EM
                                                    158.648
     3 -0.30561993D+04    1.0779747    0.0003526    160.639   178.596    EM
                                                    160.764
     4 -0.30557023D+04    0.4970284    0.0001626    160.226   177.528    EM
                                                    162.246
     5 -0.30554219D+04    0.2803728    0.0000918    160.222   176.491    EM
                                                    163.286
     6 -0.30552540D+04    0.1679298    0.0000550    160.400   175.568    EM
                                                    164.033
     7 -0.30551504D+04    0.1035349    0.0000339    160.640   174.778    EM
                                                    164.582
     8 -0.30550852D+04    0.0651983    0.0000213    160.886   174.118    EM
                                                    164.996
     9 -0.30550435D+04    0.0417617    0.0000137    161.113   173.572    EM
                                                    165.315
    10 -0.30550164D+04    0.0271152    0.0000089    161.313   173.123    EM
                                                    165.564
    11 -0.30549986D+04    0.0177893    0.0000058    161.484   172.755    EM
                                                    165.760
    12 -0.30549868D+04    0.0117628    0.0000039    161.628   172.454    EM
                                                    165.918
    13 -0.30549790D+04    0.0078213    0.0000026    161.748   172.208    EM
                                                    166.044
    14 -0.30549738D+04    0.0052221    0.0000017    161.848   172.006    EM
                                                    166.146
    15 -0.30549703D+04    0.0034971    0.0000011    161.930   171.841    EM
                                                    166.229
    16 -0.30549679D+04    0.0023467    0.0000008    161.998   171.705    EM
                                                    166.297
    17 -0.30549663D+04    0.0015773    0.0000005    162.054   171.594    EM
                                                    166.352
    18 -0.30549653D+04    0.0010613    0.0000003    162.099   171.504    EM
                                                    166.397
    19 -0.30549646D+04    0.0007148    0.0000002    162.137   171.429    EM
                                                    166.434
    20 -0.30549641D+04    0.0004817    0.0000002    162.168   171.368    EM
                                                    166.464
    21 -0.30549638D+04    0.0003248    0.0000001    162.193   171.318    EM
                                                    166.489
    22 -0.30549635D+04    0.0002191    0.0000001    162.214   171.277    EM
                                                    166.510
    23 -0.30549634D+04    0.0001478    0.0000000    162.231   171.243    EM
                                                    166.526
    24 -0.30549633D+04    0.0000998    0.0000000    162.245   171.215    EM
                                                    166.540
    25 -0.30549632D+04    0.0000674    0.0000000    162.256   171.192    EM
                                                    166.551
    26 -0.30549632D+04    0.0000455    0.0000000    162.266   171.174    EM
                                                    166.561
    27 -0.30549631D+04    0.0000307    0.0000000    162.273   171.158    EM
                                                    166.568
    28 -0.30549631D+04    0.0000207    0.0000000    162.280   171.146    EM
                                                    166.575
    29 -0.30549631D+04    0.0000140    0.0000000    162.285   171.136    EM
                                                    166.580
    30 -0.30549631D+04    0.0000094    0.0000000    162.289   171.127    EM
                                                    166.584
    31 -0.30549631D+04    0.0000064    0.0000000    162.292   171.120    EM
                                                    166.587
    32 -0.30549631D+04    0.0000043    0.0000000    162.295   171.114    EM
                                                    166.590
    33 -0.30549631D+04    0.0000029    0.0000000    162.298   171.110    EM
                                                    166.593
    34 -0.30549631D+04    0.0000020    0.0000000    162.300   171.106    EM
                                                    166.595
    35 -0.30549631D+04    0.0000013    0.0000000    162.301   171.103    EM
                                                    166.596
    36 -0.30549631D+04    0.0000024    0.0000000    162.307   171.091    FS
                                                    166.602
    37 -0.30549631D+04    0.0000003    0.0000000    162.308   171.090    FS
                                                    166.603
    38 -0.30549631D+04    0.0000000    0.0000000    162.308   171.088    FS
                                                    166.603
    39 -0.30549631D+04    0.0000000    0.0000000    162.308   171.088    FS
                                                    166.603
    40 -0.30549631D+04    0.0000000    0.0000000    162.309   171.088    FS
                                                    166.604


TECHNICAL 9 OUTPUT

  Error messages for each replication (if any)



SAVEDATA INFORMATION

  Order of variables

    Y1
    Y2
    Y3
    Y4
    C

  Save file
    ex7.22.dat

  Save file format           Free
  Save file record length    10000


     Beginning Time:  14:04:58
        Ending Time:  14:04:58
       Elapsed Time:  00:00:00



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