Mplus DEVELOPMENT (Mpdev 9/4/2025, Build 2)
MUTHEN & MUTHEN
09/05/2025  10:48 AM

INPUT INSTRUCTIONS

  Title:  Missing on X and Distal: Entropy = 0.705.

  data:
      file = ri-ltabch.dat;

  variable:
      names = u1-u18 y1-y3 w1-w27;
      usev = y1-y3;
      categorical = y1 y2;
      missing = *;

      classes = c1(3) c2(3) c3(3);

      training = w1-w27(bch);


  ANALYSIS:
      TYPE = mixture;
      proc = 16;
      starts = 0;



   MODEL:

      %overall%

    c2 on c1; c3 on c2;


    Model C3:
    %C3#1%
    [y1$1 y2$1 y2$2 y3];

    %C3#2%
    [y1$1 y2$1 y2$2 y3];

    %C3#3%
    [y1$1 y2$1 y2$2 y3];





*** WARNING in MODEL command
  All variables are uncorrelated with all other variables within class.
  Check that this is what is intended.
   1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS



Missing on X and Distal: Entropy = 0.705.

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        2000

Number of dependent variables                                    3
Number of independent variables                                  0
Number of continuous latent variables                            0
Number of categorical latent variables                           3

Observed dependent variables

  Continuous
   Y3

  Binary and ordered categorical (ordinal)
   Y1          Y2

Categorical latent variables
   C1          C2          C3

Variables with special functions

  Training variables (BCH)
   W1          W2          W3          W4          W5          W6
   W7          W8          W9          W10         W11         W12
   W13         W14         W15         W16         W17         W18
   W19         W20         W21         W22         W23         W24
   W25         W26         W27


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-03
    Relative loglikelihood change                        0.100D-05
    Derivative                                           0.100D-03
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-03
  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-03
  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
Maximum number of iterations for H1                           2000
Convergence criterion for H1                             0.100D-03
Optimization algorithm                                         EMA
Parameterization                                             LOGIT
Link                                                         LOGIT

Input data file(s)
  ri-ltabch.dat
Input data format  FREE


SUMMARY OF DATA

     Number of missing data patterns             1
     Number of y missing data patterns           1
     Number of u missing data patterns           1


COVARIANCE COVERAGE OF DATA

Minimum covariance coverage value   0.100


     PROPORTION OF DATA PRESENT FOR Y


           Covariance Coverage
              Y3
              ________
 Y3             1.000


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    Y1
      Category 1    0.505         1010.000
      Category 2    0.495          990.000
    Y2
      Category 1    0.451          901.000
      Category 2    0.058          116.000
      Category 3    0.491          983.000



UNIVARIATE SAMPLE STATISTICS


     UNIVARIATE HIGHER-ORDER MOMENT DESCRIPTIVE STATISTICS

         Variable/         Mean/     Skewness/   Minimum/ % with                Percentiles
        Sample Size      Variance    Kurtosis    Maximum  Min/Max      20%/60%    40%/80%    Median

     Y3                    0.484      -0.050      -5.710    0.05%      -1.036      0.067      0.464
            2000.000       3.197      -0.104       5.856    0.05%       0.924      1.966


THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       27

Loglikelihood

          H0 Value                      -12523.630
          H0 Scaling Correction Factor      4.4780
            for MLR

Information Criteria

          Akaike (AIC)                   25101.261
          Bayesian (BIC)                 25252.485
          Sample-Size Adjusted BIC       25166.705
            (n* = (n + 2) / 24)



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

  Latent Class
    Variable    Class

    C1             1       482.57855          0.24129
                   2       828.46832          0.41423
                   3       688.95306          0.34448
    C2             1       481.99078          0.24100
                   2       884.71887          0.44236
                   3       633.29028          0.31665
    C3             1       478.75931          0.23938
                   2       909.99377          0.45500
                   3       611.24683          0.30562


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

  Latent Class
    Pattern

    1  1  1        118.60221          0.05930
    1  1  2         33.99883          0.01700
    1  1  3         70.13729          0.03507
    1  2  1         11.69387          0.00585
    1  2  2        127.39565          0.06370
    1  2  3         45.98151          0.02299
    1  3  1         19.62358          0.00981
    1  3  2         26.84989          0.01342
    1  3  3         28.29575          0.01415
    2  1  1         79.66047          0.03983
    2  1  2         22.83569          0.01142
    2  1  3         47.10848          0.02355
    2  2  1         39.14830          0.01957
    2  2  2        426.49058          0.21325
    2  2  3        153.93525          0.07697
    2  3  1         15.56087          0.00778
    2  3  2         21.29111          0.01065
    2  3  3         22.43763          0.01122
    3  1  1         58.38453          0.02919
    3  1  2         16.73667          0.00837
    3  1  3         34.52662          0.01726
    3  2  1          5.05953          0.00253
    3  2  2         55.11965          0.02756
    3  2  3         19.89459          0.00995
    3  3  1        131.02594          0.06551
    3  3  2        179.27578          0.08964
    3  3  3        188.92974          0.09446

     Additional output is available using the TECH15 option of the OUTPUT command.


LATENT TRANSITION PROBABILITIES BASED ON THE ESTIMATED MODEL

  C1 Classes (Rows) by C2 Classes (Columns)

            1        2        3

   1     0.462    0.384    0.155
   2     0.181    0.748    0.072
   3     0.159    0.116    0.725

  C2 Classes (Rows) by C3 Classes (Columns)

            1        2        3

   1     0.532    0.153    0.315
   2     0.063    0.688    0.248
   3     0.262    0.359    0.378


TRANSITION PROBABILITY ODDS

     TRANSITION TABLE ODDS AND 95% CONFIDENCE INTERVALS FOR C1 TO C2
        1.000(1.000,1.000)   0.831(0.575,1.200)   0.336(0.159,0.707)
        0.241(0.169,0.344)   1.000(1.000,1.000)   0.096(0.035,0.259)
        0.220(0.127,0.381)   0.160(0.071,0.362)   1.000(1.000,1.000)

     TRANSITION TABLE ODDS AND 95% CONFIDENCE INTERVALS FOR C2 TO C3
        1.000(1.000,1.000)   0.287(0.145,0.565)   0.591(0.375,0.932)
        0.092(0.042,0.201)   1.000(1.000,1.000)   0.361(0.254,0.512)
        0.694(0.428,1.125)   0.949(0.594,1.515)   1.000(1.000,1.000)


C-SPECIFIC CLASSIFICATION RESULTS

Classification Quality for C1

     Entropy is not available with BCH weights.

BCH Weights for the Most Likely Latent Class Membership (Row)
by Latent Class (Column)

           1        2        3

    1   1.424    -.141    -.282
    2   -.059    1.263    -.204
    3   -.173    -.309    1.482


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

           1        2        3

    1   1.348    -.107    -.241
    2   -.078    1.328    -.250
    3   -.187    -.258    1.445


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

              1        2        3

    1     14.114    0.000    0.000
    2      0.000   14.099    0.000
    3    -14.184  -14.184    0.000

Classification Quality for C2

     Entropy is not available with BCH weights.

BCH Weights for the Most Likely Latent Class Membership (Row)
by Latent Class (Column)

           1        2        3

    1   1.377    -.136    -.241
    2   -.076    1.255    -.179
    3   -.221    -.338    1.560


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

           1        2        3

    1   1.414    -.144    -.270
    2   -.076    1.301    -.225
    3   -.189    -.260    1.448


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

              1        2        3

    1     14.162    0.000    0.000
    2      0.000   14.078    0.000
    3    -14.186  -14.186    0.000

Classification Quality for C3

     Entropy is not available with BCH weights.

BCH Weights for the Most Likely Latent Class Membership (Row)
by Latent Class (Column)

           1        2        3

    1   1.383    -.140    -.243
    2   -.060    1.240    -.180
    3   -.200    -.386    1.586


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

           1        2        3

    1   1.358    -.121    -.237
    2   -.072    1.313    -.240
    3   -.187    -.284    1.471


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

              1        2        3

    1     14.121    0.000    0.000
    2      0.000   14.088    0.000
    3    -14.202  -14.202    0.000


MODEL RESULTS

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

Parameters in the Overall Part of the Model (Parameters Equal in All of the Classes)

 Variances
    Y3                 2.711      0.104     26.176      0.000

Parameters for Class-specific Model Parts of C3

Latent Class C3#1

 Means
    Y3                -0.765      0.116     -6.589      0.000

 Thresholds
    Y1$1              -0.626      0.138     -4.549      0.000
    Y2$1              -0.447      0.131     -3.407      0.001
    Y2$2              -0.290      0.129     -2.243      0.025

Latent Class C3#2

 Means
    Y3                 1.113      0.074     15.095      0.000

 Thresholds
    Y1$1               0.373      0.090      4.147      0.000
    Y2$1               0.059      0.087      0.670      0.503
    Y2$2               0.301      0.089      3.387      0.001

Latent Class C3#3

 Means
    Y3                 0.461      0.112      4.116      0.000

 Thresholds
    Y1$1              -0.008      0.126     -0.064      0.949
    Y2$1              -0.396      0.130     -3.055      0.002
    Y2$2              -0.109      0.126     -0.859      0.390

Categorical Latent Variables

 C2#1     ON
    C1#1               2.607      0.524      4.977      0.000
    C1#2               2.441      0.689      3.542      0.000

 C2#2     ON
    C1#1               2.736      0.636      4.301      0.000
    C1#2               4.177      0.731      5.710      0.000

 C3#1     ON
    C2#1               0.891      0.385      2.314      0.021
    C2#2              -1.003      0.582     -1.723      0.085

 C3#2     ON
    C2#1              -0.672      0.541     -1.242      0.214
    C2#2               1.072      0.342      3.135      0.002

 Means
    C1#1              -0.356      0.097     -3.668      0.000
    C1#2               0.184      0.085      2.174      0.030
    C2#1              -1.516      0.281     -5.400      0.000
    C2#2              -1.830      0.415     -4.412      0.000
    C3#1              -0.366      0.247     -1.483      0.138
    C3#2              -0.052      0.239     -0.220      0.826


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.136E-03
       (ratio of smallest to largest eigenvalue)


LATENT CLASS INDICATOR MEANS AND PROBABILITIES FOR EACH LATENT CLASS

     MEAN/PROBABILITY PROFILES FOR C3
                       Latent class
                     1      2      3
     Y1
       Category 1  0.348  0.592  0.498
       Category 2  0.652  0.408  0.502
     Y2
       Category 1  0.390  0.515  0.402
       Category 2  0.038  0.060  0.071
       Category 3  0.572  0.425  0.527
     Y3           -0.765  1.113  0.461


RESULTS IN PROBABILITY SCALE

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

Results for Class-specific Model Parts of C3

Latent Class C3#1

 Y1
    Category 1         0.348      0.031     11.155      0.000
    Category 2         0.652      0.031     20.859      0.000
 Y2
    Category 1         0.390      0.031     12.502      0.000
    Category 2         0.038      0.013      2.871      0.004
    Category 3         0.572      0.032     18.076      0.000

Latent Class C3#2

 Y1
    Category 1         0.592      0.022     27.285      0.000
    Category 2         0.408      0.022     18.797      0.000
 Y2
    Category 1         0.515      0.022     23.571      0.000
    Category 2         0.060      0.010      5.789      0.000
    Category 3         0.425      0.022     19.558      0.000

Latent Class C3#3

 Y1
    Category 1         0.498      0.032     15.797      0.000
    Category 2         0.502      0.032     15.925      0.000
 Y2
    Category 1         0.402      0.031     12.916      0.000
    Category 2         0.071      0.016      4.545      0.000
    Category 3         0.527      0.032     16.723      0.000


LATENT CLASS INDICATOR ODDS RATIOS FOR THE LATENT CLASSES

                                                95% C.I.
                    Estimate       S.E.  Lower 2.5% Upper 2.5%

Results for Class-specific Model Parts of C3

Latent Class C3#1 Compared to Latent Class C3#2

 Y1
    Category > 1       2.714      0.465      1.940      3.797
 Y2
    Category > 1       1.658      0.273      1.201      2.289
    Category > 2       1.806      0.296      1.310      2.490

Latent Class C3#1 Compared to Latent Class C3#3

 Y1
    Category > 1       1.855      0.391      1.227      2.803
 Y2
    Category > 1       1.052      0.219      0.699      1.584
    Category > 2       1.199      0.245      0.803      1.790

Latent Class C3#2 Compared to Latent Class C3#3

 Y1
    Category > 1       0.683      0.122      0.481      0.970
 Y2
    Category > 1       0.635      0.114      0.446      0.904
    Category > 2       0.664      0.119      0.468      0.942


DIAGRAM INFORMATION

  Mplus diagrams are currently not available for Mixture analysis.
  No diagram output was produced.


     Beginning Time:  10:48:11
        Ending Time:  10:48:11
       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) 1998-2025 Muthen & Muthen
