Mplus VERSION 7.2
MUTHEN & MUTHEN
05/07/2014   2:42 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a LCA with binary
  	latent class indicators using user-
  	specified starting values without random
  	starts
  DATA:	FILE IS ex7.4.dat;
  VARIABLE:	NAMES ARE u1-u4 c;
  	USEVARIABLES ARE u1-u4;
  	CLASSES = c (2);
  	CATEGORICAL = u1-u4;
  ANALYSIS:	TYPE = MIXTURE;
  	STARTS = 0;
  MODEL:	
  	%OVERALL%
  	%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:	TECH1 TECH8;



INPUT READING TERMINATED NORMALLY



this is an example of a LCA with binary
latent class indicators using user-
specified starting values without random
starts

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                         500

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

Input data file(s)
  ex7.4.dat
Input data format  FREE


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U1
      Category 1    0.500      250.000
      Category 2    0.500      250.000
    U2
      Category 1    0.502      251.000
      Category 2    0.498      249.000
    U3
      Category 1    0.504      252.000
      Category 2    0.496      248.000
    U4
      Category 1    0.554      277.000
      Category 2    0.446      223.000



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                        9

Loglikelihood

          H0 Value                       -1325.213
          H0 Scaling Correction Factor      1.0142
            for MLR

Information Criteria

          Akaike (AIC)                    2668.425
          Bayesian (BIC)                  2706.357
          Sample-Size Adjusted BIC        2677.790
            (n* = (n + 2) / 24)

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

          Pearson Chi-Square

          Value                             12.611
          Degrees of Freedom                     6
          P-Value                           0.0496

          Likelihood Ratio Chi-Square

          Value                             12.742
          Degrees of Freedom                     6
          P-Value                           0.0473



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


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

           1        2

    1   0.888    0.112
    2   0.186    0.814


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

              1        2

    1      2.066    0.000
    2     -1.475    0.000


MODEL RESULTS

                                                    Two-Tailed
                    Estimate       S.E.  Est./S.E.    P-Value

Latent Class 1

 Thresholds
    U1$1               1.221      0.243      5.028      0.000
    U2$1               1.086      0.273      3.977      0.000
    U3$1              -0.906      0.190     -4.775      0.000
    U4$1              -0.511      0.224     -2.282      0.022

Latent Class 2

 Thresholds
    U1$1              -1.287      0.344     -3.735      0.000
    U2$1              -1.119      0.239     -4.674      0.000
    U3$1               0.990      0.260      3.813      0.000
    U4$1               1.048      0.179      5.847      0.000

Categorical Latent Variables

 Means
    C#1                0.041      0.254      0.161      0.872


RESULTS IN PROBABILITY SCALE

Latent Class 1

 U1
    Category 1         0.772      0.043     18.081      0.000
    Category 2         0.228      0.043      5.334      0.000
 U2
    Category 1         0.748      0.052     14.513      0.000
    Category 2         0.252      0.052      4.901      0.000
 U3
    Category 1         0.288      0.039      7.402      0.000
    Category 2         0.712      0.039     18.312      0.000
 U4
    Category 1         0.375      0.052      7.149      0.000
    Category 2         0.625      0.052     11.914      0.000

Latent Class 2

 U1
    Category 1         0.216      0.058      3.705      0.000
    Category 2         0.784      0.058     13.413      0.000
 U2
    Category 1         0.246      0.044      5.541      0.000
    Category 2         0.754      0.044     16.966      0.000
 U3
    Category 1         0.729      0.051     14.216      0.000
    Category 2         0.271      0.051      5.280      0.000
 U4
    Category 1         0.740      0.034     21.491      0.000
    Category 2         0.260      0.034      7.533      0.000


LATENT CLASS ODDS RATIO RESULTS

Latent Class 1 Compared to Latent Class 2

 U1
    Category > 1       0.081      0.033      2.492      0.013
 U2
    Category > 1       0.110      0.038      2.882      0.004
 U3
    Category > 1       6.662      2.094      3.181      0.001
 U4
    Category > 1       4.754      1.458      3.261      0.001


QUALITY OF NUMERICAL RESULTS

     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


           LAMBDA(U)
              C#1           C#2
              ________      ________
 U1                 1             2
 U2                 3             4
 U3                 5             6
 U4                 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


           LAMBDA(U)
              C#1           C#2
              ________      ________
 U1            -1.000         1.000
 U2            -1.000         1.000
 U3             1.000        -1.000
 U4             1.000        -1.000


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


TECHNICAL 8 OUTPUT


  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


     Beginning Time:  14:42:20
        Ending Time:  14:42:20
       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) 1998-2014 Muthen & Muthen

Back to examples