Mplus VERSION 7
MUTHEN & MUTHEN
09/22/2012  10:56 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a LCA with binary,
  	censored, unordered, and count latent
  	class indicators using user-specified
  	starting values without random starts
  DATA:	FILE IS ex7.11.dat;
  VARIABLE:	NAMES ARE u3 y1 u2 u1 c;
  	USEVARIABLES ARE u3-u1;
  	CLASSES = c (2);
  	CATEGORICAL = u1;
  	CENSORED = y1 (b);
  	NOMINAL = u2;
  	COUNT = u3 (i);
  ANALYSIS:	TYPE = MIXTURE;
  	STARTS = 0;
  MODEL:	
  	%OVERALL%
  	%c#1%
  	[u1$1*-1 y1*3 u2#1*0 u2#2*1 u3*.5 u3#1*1.5];
  	y1*2;
  	%c#2%
  	[u1$1*0 y1*1 u2#1*-1 u2#2*0 u3*1 u3#1*1];
  	y1*1;
  OUTPUT:	TECH1 TECH8;



INPUT READING TERMINATED NORMALLY



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

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        1000

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

  Censored
   Y1

  Binary and ordered categorical (ordinal)
   U1

  Unordered categorical (nominal)
   U2

  Count
   U3

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)
  ex7.11.dat
Input data format  FREE


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U1
      Category 1    0.383      383.000
      Category 2    0.617      617.000
    U2
      Category 1    0.203      203.000
      Category 2    0.513      513.000
      Category 3    0.284      284.000


SUMMARY OF CENSORED LIMITS

      Y1                 0.000


COUNT PROPORTION OF ZERO, MINIMUM AND MAXIMUM VALUES

      U3          0.796         0         7



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       15

Loglikelihood

          H0 Value                       -4348.434
          H0 Scaling Correction Factor      0.9935
            for MLR

Information Criteria

          Akaike (AIC)                    8726.869
          Bayesian (BIC)                  8800.485
          Sample-Size Adjusted BIC        8752.844
            (n* = (n + 2) / 24)

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

          Pearson Chi-Square

          Value                              0.000
          Degrees of freedom cannot be computed for this model part.

          Likelihood Ratio Chi-Square

          Value                              0.000
          Degrees of freedom cannot be computed for this model part.



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

    Latent
   Classes

       1        621.01520          0.62102
       2        378.98480          0.37898


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

    Latent
   Classes

       1        621.01529          0.62102
       2        378.98471          0.37898


CLASSIFICATION QUALITY

     Entropy                         0.369


CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP

Class Counts and Proportions

    Latent
   Classes

       1              582          0.58200
       2              418          0.41800


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

           1        2

    1   0.843    0.157
    2   0.312    0.688


MODEL RESULTS

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

Latent Class 1

 Means
    U3#1               1.505      0.163      9.245      0.000
    U3                 0.726      0.103      7.066      0.000
    Y1                 2.735      0.207     13.243      0.000
    U2#1              -0.006      0.163     -0.037      0.971
    U2#2               0.960      0.145      6.639      0.000

 Thresholds
    U1$1              -0.756      0.136     -5.545      0.000

 Variances
    Y1                 2.332      0.317      7.349      0.000

Latent Class 2

 Means
    U3#1               0.826      0.180      4.584      0.000
    U3                 0.897      0.075     11.978      0.000
    Y1                 0.939      0.141      6.674      0.000
    U2#1              -0.772      0.241     -3.197      0.001
    U2#2               0.076      0.208      0.365      0.715

 Thresholds
    U1$1              -0.053      0.180     -0.292      0.770

 Variances
    Y1                 0.991      0.213      4.651      0.000

Categorical Latent Variables

 Means
    C#1                0.494      0.344      1.435      0.151


RESULTS IN PROBABILITY SCALE

Latent Class 1

 U1
    Category 1         0.320      0.030     10.787      0.000
    Category 2         0.680      0.030     22.964      0.000

Latent Class 2

 U1
    Category 1         0.487      0.045     10.843      0.000
    Category 2         0.513      0.045     11.428      0.000


LATENT CLASS ODDS RATIO RESULTS

Latent Class 1 Compared to Latent Class 2

 U1
    Category > 1       2.020      0.528      3.828      0.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.481E-02
       (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
              ________
 1                  1


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


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


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


     PARAMETER SPECIFICATION FOR THE CENSORED/NOMINAL/COUNT MODEL PART


           NU(P) FOR LATENT CLASS 1
              U3#1          U3            Y1#1          Y1            U2#1
              ________      ________      ________      ________      ________
 1                  4             5             0             6             7


           NU(P) FOR LATENT CLASS 1
              U2#2
              ________
 1                  8


           THETA(C) FOR CLASS LATENT CLASS 1
              Y1
              ________
 1                  9


           NU(P) FOR LATENT CLASS 2
              U3#1          U3            Y1#1          Y1            U2#1
              ________      ________      ________      ________      ________
 1                 10            11             0            12            13


           NU(P) FOR LATENT CLASS 2
              U2#2
              ________
 1                 14


           THETA(C) FOR CLASS LATENT CLASS 2
              Y1
              ________
 1                 15


     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
              ________
 1             -1.000


           TAU(U) FOR LATENT CLASS 2
              U1$1
              ________
 1              0.000


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


     STARTING VALUES FOR THE CENSORED/NOMINAL/COUNT MODEL PART


           NU(P) FOR LATENT CLASS 1
              U3#1          U3            Y1#1          Y1            U2#1
              ________      ________      ________      ________      ________
 1              1.500         0.500       -20.000         3.000         0.000


           NU(P) FOR LATENT CLASS 1
              U2#2
              ________
 1              1.000


           THETA(C) FOR LATENT CLASS 1
              Y1
              ________
 1              2.000


           NU(P) FOR LATENT CLASS 2
              U3#1          U3            Y1#1          Y1            U2#1
              ________      ________      ________      ________      ________
 1              1.000         1.000       -20.000         1.000        -1.000


           NU(P) FOR LATENT CLASS 2
              U2#2
              ________
 1              0.000


           THETA(C) FOR LATENT CLASS 2
              Y1
              ________
 1              1.000


TECHNICAL 8 OUTPUT


  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE      CLASS COUNTS    ALGORITHM
     1 -0.43579548D+04    0.0000000    0.0000000    518.989   481.011    EM
     2 -0.43501136D+04    7.8411567    0.0017993    521.014   478.986    EM
     3 -0.43491950D+04    0.9186629    0.0002112    522.482   477.518    EM
     4 -0.43489540D+04    0.2409893    0.0000554    523.738   476.262    EM
     5 -0.43488802D+04    0.0737856    0.0000170    524.904   475.096    EM
     6 -0.43488517D+04    0.0284651    0.0000065    526.025   473.975    EM
     7 -0.43488364D+04    0.0153532    0.0000035    527.121   472.879    EM
     8 -0.43488251D+04    0.0112674    0.0000026    528.201   471.799    EM
     9 -0.43488153D+04    0.0098209    0.0000023    529.267   470.733    EM
    10 -0.43488061D+04    0.0091792    0.0000021    530.322   469.678    EM
    11 -0.43487973D+04    0.0087980    0.0000020    531.366   468.634    EM
    12 -0.43487888D+04    0.0085104    0.0000020    532.400   467.600    EM
    13 -0.43487805D+04    0.0082631    0.0000019    533.424   466.576    EM
    14 -0.43487725D+04    0.0080376    0.0000018    534.438   465.562    EM
    15 -0.43487647D+04    0.0078270    0.0000018    535.442   464.558    EM
    16 -0.43487570D+04    0.0076277    0.0000018    536.436   463.564    EM
    17 -0.43487496D+04    0.0074381    0.0000017    537.421   462.579    EM
    18 -0.43487423D+04    0.0072566    0.0000017    538.395   461.605    EM
    19 -0.43487353D+04    0.0070825    0.0000016    539.360   460.640    EM
    20 -0.43487283D+04    0.0069148    0.0000016    540.315   459.685    EM
    21 -0.43487216D+04    0.0067529    0.0000016    541.261   458.739    EM
    22 -0.43487150D+04    0.0065963    0.0000015    542.196   457.804    EM
    23 -0.43487085D+04    0.0064445    0.0000015    543.123   456.877    EM
    24 -0.43487022D+04    0.0062972    0.0000014    544.039   455.961    EM
    25 -0.43486961D+04    0.0061541    0.0000014    544.946   455.054    EM
    26 -0.43486901D+04    0.0060148    0.0000014    545.843   454.157    EM
    27 -0.43486842D+04    0.0058792    0.0000014    546.731   453.269    EM
    28 -0.43486784D+04    0.0057471    0.0000013    547.610   452.390    EM
    29 -0.43486728D+04    0.0056182    0.0000013    548.479   451.521    EM
    30 -0.43486673D+04    0.0054925    0.0000013    549.339   450.661    EM
    31 -0.43486620D+04    0.0053697    0.0000012    550.190   449.810    EM
    32 -0.43486567D+04    0.0052499    0.0000012    551.032   448.968    EM
    33 -0.43486516D+04    0.0051328    0.0000012    551.865   448.135    EM
    34 -0.43486466D+04    0.0050184    0.0000012    552.689   447.311    EM
    35 -0.43486417D+04    0.0049065    0.0000011    553.504   446.496    EM
    36 -0.43486369D+04    0.0047972    0.0000011    554.310   445.690    EM
    37 -0.43486322D+04    0.0046903    0.0000011    555.108   444.892    EM
    38 -0.43486276D+04    0.0045858    0.0000011    555.897   444.103    EM
    39 -0.43486231D+04    0.0044836    0.0000010    556.677   443.323    EM
    40 -0.43486187D+04    0.0043836    0.0000010    557.449   442.551    EM
    41 -0.43486144D+04    0.0042858    0.0000010    558.212   441.788    EM
    42 -0.43486102D+04    0.0041902    0.0000010    558.967   441.033    EM
    43 -0.43486061D+04    0.0040966    0.0000009    559.714   440.286    EM
    44 -0.43486021D+04    0.0040051    0.0000009    560.452   439.548    EM
    45 -0.43485982D+04    0.0039155    0.0000009    561.183   438.817    EM
    46 -0.43485944D+04    0.0038279    0.0000009    561.905   438.095    EM
    47 -0.43485907D+04    0.0037422    0.0000009    562.619   437.381    EM
    48 -0.43485870D+04    0.0036583    0.0000008    563.326   436.674    EM
    49 -0.43485834D+04    0.0035763    0.0000008    564.024   435.976    EM
    50 -0.43485799D+04    0.0034960    0.0000008    564.715   435.285    EM
    51 -0.43485765D+04    0.0034174    0.0000008    565.398   434.602    EM
    52 -0.43485732D+04    0.0033406    0.0000008    566.074   433.926    EM
    53 -0.43485699D+04    0.0032654    0.0000008    566.742   433.258    EM
    54 -0.43485667D+04    0.0031918    0.0000007    567.403   432.597    EM
    55 -0.43485636D+04    0.0031198    0.0000007    568.056   431.944    EM
    56 -0.43485605D+04    0.0030494    0.0000007    568.702   431.298    EM
    57 -0.43485576D+04    0.0029805    0.0000007    569.340   430.660    EM
    58 -0.43485546D+04    0.0029131    0.0000007    569.972   430.028    EM
    59 -0.43485518D+04    0.0028471    0.0000007    570.596   429.404    EM
    60 -0.43484345D+04    0.1173271    0.0000270    621.015   378.985    QN
    61 -0.43484345D+04    0.0000000    0.0000000    621.015   378.985    EM


     Beginning Time:  22:56:59
        Ending Time:  22:56:59
       Elapsed Time:  00:00:00



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