Mplus VERSION 7
MUTHEN & MUTHEN
09/22/2012  10:03 PM

INPUT INSTRUCTIONS

  title:
  	this is an example of a LCA with binary
  	latent class indicators using automatic
  	starting values with random starts
  	!same as ex7.3 and ex7.4

  montecarlo:
  	names are u1-u4;
  	generate = u1-u4(1);
  	categorical = u1-u4;
  	genclasses = c(2);
  	classes = c(2);
  	nobs = 500;
  	seed = 3454367;
  	nrep = 1;
  	save = ex7.5.dat;

  analysis:
  	type = mixture;


  model population:

  	%overall%

  	[c#1*0];
  	
  	%c#1%
  	[u1$1*1 u2$1*1 u3$1*-1 u4$1*-1];

  	%c#2%
  	[u1$1*-1 u2$1*-1 u3$1*1 u4$1*1];

  model:

  	%overall%

  	[c#1*0];
  	
  	%c#1%
  	[u1$1*1 u2$1*1 u3$1*-1 u4$1*-1];

  	%c#2%
  	[u1$1*-1 u2$1*-1 u3$1*1 u4$1*1];

  output:
  	tech8 tech9;
  	
  	
  	

  	
  	



INPUT READING TERMINATED NORMALLY




this is an example of a LCA with binary
latent class indicators using automatic
starting values with random starts

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

  Binary and ordered categorical (ordinal)
   U1          U2          U3          U4

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                        9

Loglikelihood

    H0 Value

        Mean                             -1325.213
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000        -1325.213      -1325.213
           0.980       0.000        -1325.213      -1325.213
           0.950       0.000        -1325.213      -1325.213
           0.900       0.000        -1325.213      -1325.213
           0.800       0.000        -1325.213      -1325.213
           0.700       0.000        -1325.213      -1325.213
           0.500       0.000        -1325.213      -1325.213
           0.300       0.000        -1325.213      -1325.213
           0.200       0.000        -1325.213      -1325.213
           0.100       0.000        -1325.213      -1325.213
           0.050       0.000        -1325.213      -1325.213
           0.020       0.000        -1325.213      -1325.213
           0.010       0.000        -1325.213      -1325.213

Information Criteria

    Akaike (AIC)

        Mean                              2668.425
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         2668.425       2668.425
           0.980       0.000         2668.425       2668.425
           0.950       0.000         2668.425       2668.425
           0.900       0.000         2668.425       2668.425
           0.800       0.000         2668.425       2668.425
           0.700       0.000         2668.425       2668.425
           0.500       0.000         2668.425       2668.425
           0.300       0.000         2668.425       2668.425
           0.200       0.000         2668.425       2668.425
           0.100       0.000         2668.425       2668.425
           0.050       0.000         2668.425       2668.425
           0.020       0.000         2668.425       2668.425
           0.010       0.000         2668.425       2668.425

    Bayesian (BIC)

        Mean                              2706.357
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         2706.357       2706.357
           0.980       0.000         2706.357       2706.357
           0.950       0.000         2706.357       2706.357
           0.900       0.000         2706.357       2706.357
           0.800       0.000         2706.357       2706.357
           0.700       0.000         2706.357       2706.357
           0.500       0.000         2706.357       2706.357
           0.300       0.000         2706.357       2706.357
           0.200       0.000         2706.357       2706.357
           0.100       0.000         2706.357       2706.357
           0.050       0.000         2706.357       2706.357
           0.020       0.000         2706.357       2706.357
           0.010       0.000         2706.357       2706.357

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

        Mean                              2677.790
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         2677.790       2677.790
           0.980       0.000         2677.790       2677.790
           0.950       0.000         2677.790       2677.790
           0.900       0.000         2677.790       2677.790
           0.800       0.000         2677.790       2677.790
           0.700       0.000         2677.790       2677.790
           0.500       0.000         2677.790       2677.790
           0.300       0.000         2677.790       2677.790
           0.200       0.000         2677.790       2677.790
           0.100       0.000         2677.790       2677.790
           0.050       0.000         2677.790       2677.790
           0.020       0.000         2677.790       2677.790
           0.010       0.000         2677.790       2677.790

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

    Pearson Chi-Square

        Mean                                12.611
        Std Dev                              0.000
        Degrees of freedom                       6
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       1.000            0.872         12.611
           0.980       1.000            1.134         12.611
           0.950       1.000            1.635         12.611
           0.900       1.000            2.204         12.611
           0.800       1.000            3.070         12.611
           0.700       1.000            3.828         12.611
           0.500       1.000            5.348         12.611
           0.300       1.000            7.231         12.611
           0.200       1.000            8.558         12.611
           0.100       1.000           10.645         12.611
           0.050       1.000           12.592         12.611
           0.020       0.000           15.033         12.611
           0.010       0.000           16.812         12.611

    Likelihood Ratio Chi-Square

        Mean                                12.742
        Std Dev                              0.000
        Degrees of freedom                       6
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       1.000            0.872         12.742
           0.980       1.000            1.134         12.742
           0.950       1.000            1.635         12.742
           0.900       1.000            2.204         12.742
           0.800       1.000            3.070         12.742
           0.700       1.000            3.828         12.742
           0.500       1.000            5.348         12.742
           0.300       1.000            7.231         12.742
           0.200       1.000            8.558         12.742
           0.100       1.000           10.645         12.742
           0.050       1.000           12.592         12.742
           0.020       0.000           15.033         12.742
           0.010       0.000           16.812         12.742



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

    Latent
   Classes

       1        255.11204          0.51022
       2        244.88796          0.48978


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

    Latent
   Classes

       1        255.11204          0.51022
       2        244.88796          0.48978


CLASSIFICATION QUALITY

     Entropy                         0.504


CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP

Class Counts and Proportions

    Latent
   Classes

       1              272          0.54400
       2              228          0.45600


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

           1        2

    1   0.832    0.168
    2   0.126    0.874


MODEL RESULTS

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

 Thresholds
  U1$1             1.000     1.2208     0.0000     0.2428     0.0487 1.000 1.000
  U2$1             1.000     1.0856     0.0000     0.2730     0.0073 1.000 1.000
  U3$1            -1.000    -0.9059     0.0000     0.1897     0.0089 1.000 1.000
  U4$1            -1.000    -0.5107     0.0000     0.2238     0.2394 0.000 1.000

Latent Class 2

 Thresholds
  U1$1            -1.000    -1.2865     0.0000     0.3444     0.0821 1.000 1.000
  U2$1            -1.000    -1.1190     0.0000     0.2394     0.0142 1.000 1.000
  U3$1             1.000     0.9905     0.0000     0.2597     0.0001 1.000 1.000
  U4$1             1.000     1.0483     0.0000     0.1793     0.0023 1.000 1.000

Categorical Latent Variables

 Means
  C#1              0.000     0.0409     0.0000     0.2536     0.0017 1.000 0.000


QUALITY OF NUMERICAL RESULTS

     Average Condition Number for the Information Matrix      0.421E-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          U2$1          U3$1          U4$1
              ________      ________      ________      ________
 1                  1             2             3             4


           TAU(U) FOR LATENT CLASS 2
              U1$1          U2$1          U3$1          U4$1
              ________      ________      ________      ________
 1                  5             6             7             8


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2
              ________      ________
 1                  9             0


     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          U2$1          U3$1          U4$1
              ________      ________      ________      ________
 1              1.000         1.000        -1.000        -1.000


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


     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          U2$1          U3$1          U4$1
              ________      ________      ________      ________
 1              1.000         1.000        -1.000        -1.000


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


TECHNICAL 8 OUTPUT


  TECHNICAL 8 OUTPUT FOR REPLICATION 1


  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE      CLASS COUNTS    ALGORITHM
     1 -0.13308427D+04    0.0000000    0.0000000    242.133   257.867    EM
     2 -0.13261044D+04    4.7383081    0.0035604    242.465   257.535    EM
     3 -0.13255717D+04    0.5326802    0.0004017    242.969   257.031    EM
     4 -0.13253885D+04    0.1831222    0.0001381    243.554   256.446    EM
     5 -0.13253222D+04    0.0663120    0.0000500    244.168   255.832    EM
     6 -0.13252942D+04    0.0280563    0.0000212    244.782   255.218    EM
     7 -0.13252792D+04    0.0149917    0.0000113    245.381   254.619    EM
     8 -0.13252692D+04    0.0099642    0.0000075    245.957   254.043    EM
     9 -0.13252616D+04    0.0076148    0.0000057    246.507   253.493    EM
    10 -0.13252554D+04    0.0062499    0.0000047    247.028   252.972    EM
    11 -0.13252501D+04    0.0053068    0.0000040    247.522   252.478    EM
    12 -0.13252455D+04    0.0045809    0.0000035    247.987   252.013    EM
    13 -0.13252415D+04    0.0039878    0.0000030    248.426   251.574    EM
    14 -0.13252380D+04    0.0034873    0.0000026    248.839   251.161    EM
    15 -0.13252349D+04    0.0030574    0.0000023    249.227   250.773    EM
    16 -0.13252323D+04    0.0026844    0.0000020    249.592   250.408    EM
    17 -0.13252299D+04    0.0023588    0.0000018    249.934   250.066    EM
    18 -0.13252278D+04    0.0020738    0.0000016    250.256   249.744    EM
    19 -0.13252260D+04    0.0018236    0.0000014    250.558   249.442    EM
    20 -0.13252244D+04    0.0016038    0.0000012    250.842   249.158    EM
    21 -0.13252230D+04    0.0014106    0.0000011    251.108   248.892    EM
    22 -0.13252217D+04    0.0012407    0.0000009    251.358   248.642    EM
    23 -0.13252207D+04    0.0010912    0.0000008    251.592   248.408    EM
    24 -0.13252197D+04    0.0009598    0.0000007    251.811   248.189    EM
    25 -0.13252188D+04    0.0008441    0.0000006    252.017   247.983    EM
    26 -0.13252181D+04    0.0007424    0.0000006    252.211   247.789    EM
    27 -0.13252175D+04    0.0006529    0.0000005    252.392   247.608    EM
    28 -0.13252169D+04    0.0005741    0.0000004    252.562   247.438    EM
    29 -0.13252164D+04    0.0005049    0.0000004    252.721   247.279    EM
    30 -0.13252159D+04    0.0004439    0.0000003    252.870   247.130    EM
    31 -0.13252155D+04    0.0003904    0.0000003    253.011   246.989    EM
    32 -0.13252152D+04    0.0003432    0.0000003    253.142   246.858    EM
    33 -0.13252149D+04    0.0003018    0.0000002    253.265   246.735    EM
    34 -0.13252146D+04    0.0002653    0.0000002    253.381   246.619    EM
    35 -0.13252144D+04    0.0002333    0.0000002    253.489   246.511    EM
    36 -0.13252142D+04    0.0002051    0.0000002    253.591   246.409    EM
    37 -0.13252140D+04    0.0001803    0.0000001    253.686   246.314    EM
    38 -0.13252128D+04    0.0011615    0.0000009    255.175   244.825    FS
    39 -0.13252127D+04    0.0001294    0.0000001    254.952   245.048    FS
    40 -0.13252127D+04    0.0000172    0.0000000    255.132   244.868    FS
    41 -0.13252127D+04    0.0000024    0.0000000    255.093   244.907    FS
    42 -0.13252127D+04    0.0000003    0.0000000    255.119   244.881    FS
    43 -0.13252127D+04    0.0000000    0.0000000    255.112   244.888    FS


TECHNICAL 9 OUTPUT

  Error messages for each replication (if any)



SAVEDATA INFORMATION

  Order of variables

    U1
    U2
    U3
    U4
    C

  Save file
    ex7.5.dat

  Save file format           Free
  Save file record length    10000


     Beginning Time:  22:03:27
        Ending Time:  22:03:27
       Elapsed Time:  00:00:00



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

Tel: (310) 391-9971
Fax: (310) 391-8971
Web: www.StatModel.com
Support: Support@StatModel.com

Copyright (c) 1998-2012 Muthen & Muthen

Back to examples