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

INPUT INSTRUCTIONS

  TITLE:
  	this is an example of mixture modeling
  	with known classes (multiple group
  	analysis)

  montecarlo:
  	names are y1-y4 g;
  	generate = g(1);
  	categorical = g;
  	genclasses = cg(2) c(2);
  	classes = cg(2) c(2);
  	nobs = 1000;
  	seed = 3454367;
  	nrep = 1;
  	save = ex7.21.dat;

  ANALYSIS:
  	TYPE = MIXTURE;

  MODEL POPULATION:
  	%OVERALL%
  	c#1 on cg#1*1;

  MODEL POPULATION-c:
  	%c#1%
  	[y1-y4*-1];
  	%c#2%
  	[y1-y4*1];

  MODEL POPULATION-cg:
  	%cg#1%
  	[g$1@15];
  	y1-y4*1;
  	%cg#2%
  	[g$1@-15];
  	y1-y4*.5;

  MODEL:
  	%OVERALL%
  	c#1 on cg#1*1;

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

  MODEL cg:
  	%cg#1%
  	[g$1@15];
  	y1-y4*1;
  	%cg#2%
  	[g$1@-15];
  	y1-y4*.5;

  OUTPUT:
  	TECH8;



*** 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




this is an example of mixture modeling
with known classes (multiple group
analysis)

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        1000

Number of replications
    Requested                                                    1
    Completed                                                    1
Value of seed                                              3454367

Number of dependent variables                                    5
Number of independent variables                                  0
Number of continuous latent variables                            0
Number of categorical latent variables                           2

Observed dependent variables

  Continuous
   Y1          Y2          Y3          Y4

  Binary and ordered categorical (ordinal)
   G

Categorical latent variables
   CG          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
Parameterization                                             LOGIT
Link                                                         LOGIT


SAMPLE STATISTICS FOR THE FIRST REPLICATION


     SAMPLE STATISTICS


           Means
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1             -0.239        -0.261        -0.262        -0.256


           Covariances
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.630
 Y2             0.821         1.543
 Y3             0.870         0.869         1.690
 Y4             0.852         0.902         0.934         1.706


           Correlations
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.518         1.000
 Y3             0.524         0.538         1.000
 Y4             0.511         0.556         0.550         1.000




MODEL FIT INFORMATION

Number of Free Parameters                       19

Loglikelihood

    H0 Value

        Mean                             -6273.830
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000        -6273.830      -6273.830
           0.980       0.000        -6273.830      -6273.830
           0.950       0.000        -6273.830      -6273.830
           0.900       0.000        -6273.830      -6273.830
           0.800       0.000        -6273.830      -6273.830
           0.700       0.000        -6273.830      -6273.830
           0.500       0.000        -6273.830      -6273.830
           0.300       0.000        -6273.830      -6273.830
           0.200       0.000        -6273.830      -6273.830
           0.100       0.000        -6273.830      -6273.830
           0.050       0.000        -6273.830      -6273.830
           0.020       0.000        -6273.830      -6273.830
           0.010       0.000        -6273.830      -6273.830

Information Criteria

    Akaike (AIC)

        Mean                             12585.660
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000        12585.660      12585.660
           0.980       0.000        12585.660      12585.660
           0.950       0.000        12585.660      12585.660
           0.900       0.000        12585.660      12585.660
           0.800       0.000        12585.660      12585.660
           0.700       0.000        12585.660      12585.660
           0.500       0.000        12585.660      12585.660
           0.300       0.000        12585.660      12585.660
           0.200       0.000        12585.660      12585.660
           0.100       0.000        12585.660      12585.660
           0.050       0.000        12585.660      12585.660
           0.020       0.000        12585.660      12585.660
           0.010       0.000        12585.660      12585.660

    Bayesian (BIC)

        Mean                             12678.907
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000        12678.907      12678.907
           0.980       0.000        12678.907      12678.907
           0.950       0.000        12678.907      12678.907
           0.900       0.000        12678.907      12678.907
           0.800       0.000        12678.907      12678.907
           0.700       0.000        12678.907      12678.907
           0.500       0.000        12678.907      12678.907
           0.300       0.000        12678.907      12678.907
           0.200       0.000        12678.907      12678.907
           0.100       0.000        12678.907      12678.907
           0.050       0.000        12678.907      12678.907
           0.020       0.000        12678.907      12678.907
           0.010       0.000        12678.907      12678.907

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

        Mean                             12618.562
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000        12618.562      12618.562
           0.980       0.000        12618.562      12618.562
           0.950       0.000        12618.562      12618.562
           0.900       0.000        12618.562      12618.562
           0.800       0.000        12618.562      12618.562
           0.700       0.000        12618.562      12618.562
           0.500       0.000        12618.562      12618.562
           0.300       0.000        12618.562      12618.562
           0.200       0.000        12618.562      12618.562
           0.100       0.000        12618.562      12618.562
           0.050       0.000        12618.562      12618.562
           0.020       0.000        12618.562      12618.562
           0.010       0.000        12618.562      12618.562

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

    Pearson Chi-Square

        Mean                                 0.000
        Std Dev                              0.000
        Degrees of freedom                       0
        Number of successful computations        1

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

    Likelihood Ratio Chi-Square

        Mean                                 0.000
        Std Dev                              0.000
        Degrees of freedom                       0
        Number of successful computations        1

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



MODEL RESULTS USE THE LATENT CLASS VARIABLE ORDER

   CG  C

  Latent Class Variable Patterns

         CG         C
      Class     Class

         1         1
         1         2
         2         1
         2         2


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

  Latent Class
    Pattern

   1 1        386.99769          0.38700
   1 2        126.00232          0.12600
   2 1        235.02303          0.23502
   2 2        251.97696          0.25198


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

  Latent Class
    Variable    Class

    CG             1       513.00000          0.51300
                   2       487.00000          0.48700
    C              1       622.02069          0.62202
                   2       377.97928          0.37798


LATENT TRANSITION PROBABILITIES BASED ON THE ESTIMATED MODEL

  CG Classes (Rows) by C Classes (Columns)

            1        2

   1     0.754    0.246
   2     0.483    0.517


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

  Latent Class
    Pattern

   1 1        386.99763          0.38700
   1 2        126.00238          0.12600
   2 1        235.02304          0.23502
   2 2        251.97695          0.25198


FINAL CLASS COUNTS AND PROPORTIONS FOR EACH LATENT CLASS VARIABLE
BASED ON ESTIMATED POSTERIOR PROBABILITIES

  Latent Class
    Variable    Class

    CG             1       513.00000          0.51300
                   2       487.00000          0.48700
    C              1       622.02063          0.62202
                   2       377.97931          0.37798


CLASSIFICATION QUALITY

     Entropy                         0.980


CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS PATTERN

Class Counts and Proportions

  Latent Class
    Pattern

   1 1              387          0.38700
   1 2              126          0.12600
   2 1              235          0.23500
   2 2              252          0.25200


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

  Latent Class Variable Patterns

  Latent Class         CG         C
   Pattern No.      Class     Class

         1             1         1
         2             1         2
         3             2         1
         4             2         2

           1        2        3        4

    1   0.990    0.010    0.000    0.000
    2   0.030    0.970    0.000    0.000
    3   0.000    0.000    0.998    0.002
    4   0.000    0.000    0.002    0.998


CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP
FOR EACH LATENT CLASS VARIABLE

  Latent Class
    Variable    Class

    CG             1             513          0.51300
                   2             487          0.48700
    C              1             622          0.62200
                   2             378          0.37800


MODEL RESULTS

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

 Means
  Y1              -1.000    -0.9596     0.0000     0.0359     0.0016 1.000 1.000
  Y2              -1.000    -0.9574     0.0000     0.0333     0.0018 1.000 1.000
  Y3              -1.000    -1.0097     0.0000     0.0343     0.0001 1.000 1.000
  Y4              -1.000    -1.0405     0.0000     0.0336     0.0016 1.000 1.000

 Thresholds
  G$1             15.000    15.0000     0.0000     0.0000     0.0000 1.000 0.000

 Variances
  Y1               1.000     1.0205     0.0000     0.0660     0.0004 1.000 1.000
  Y2               1.000     0.9857     0.0000     0.0647     0.0002 1.000 1.000
  Y3               1.000     0.9902     0.0000     0.0626     0.0001 1.000 1.000
  Y4               1.000     1.0008     0.0000     0.0603     0.0000 1.000 1.000

Latent Class Pattern 1 2

 Means
  Y1               1.000     0.9381     0.0000     0.0415     0.0038 1.000 1.000
  Y2               1.000     0.9049     0.0000     0.0386     0.0090 0.000 1.000
  Y3               1.000     0.9704     0.0000     0.0414     0.0009 1.000 1.000
  Y4               1.000     1.0084     0.0000     0.0399     0.0001 1.000 1.000

 Thresholds
  G$1             15.000    15.0000     0.0000     0.0000     0.0000 1.000 0.000

 Variances
  Y1               1.000     1.0205     0.0000     0.0660     0.0004 1.000 1.000
  Y2               1.000     0.9857     0.0000     0.0647     0.0002 1.000 1.000
  Y3               1.000     0.9902     0.0000     0.0626     0.0001 1.000 1.000
  Y4               1.000     1.0008     0.0000     0.0603     0.0000 1.000 1.000

Latent Class Pattern 2 1

 Means
  Y1              -1.000    -0.9596     0.0000     0.0359     0.0016 1.000 1.000
  Y2              -1.000    -0.9574     0.0000     0.0333     0.0018 1.000 1.000
  Y3              -1.000    -1.0097     0.0000     0.0343     0.0001 1.000 1.000
  Y4              -1.000    -1.0405     0.0000     0.0336     0.0016 1.000 1.000

 Thresholds
  G$1            -15.000   -15.0000     0.0000     0.0000     0.0000 1.000 0.000

 Variances
  Y1               0.500     0.5513     0.0000     0.0352     0.0026 1.000 1.000
  Y2               0.500     0.4468     0.0000     0.0270     0.0028 0.000 1.000
  Y3               0.500     0.5139     0.0000     0.0315     0.0002 1.000 1.000
  Y4               0.500     0.4646     0.0000     0.0301     0.0013 1.000 1.000

Latent Class Pattern 2 2

 Means
  Y1               1.000     0.9381     0.0000     0.0415     0.0038 1.000 1.000
  Y2               1.000     0.9049     0.0000     0.0386     0.0090 0.000 1.000
  Y3               1.000     0.9704     0.0000     0.0414     0.0009 1.000 1.000
  Y4               1.000     1.0084     0.0000     0.0399     0.0001 1.000 1.000

 Thresholds
  G$1            -15.000   -15.0000     0.0000     0.0000     0.0000 1.000 0.000

 Variances
  Y1               0.500     0.5513     0.0000     0.0352     0.0026 1.000 1.000
  Y2               0.500     0.4468     0.0000     0.0270     0.0028 0.000 1.000
  Y3               0.500     0.5139     0.0000     0.0315     0.0002 1.000 1.000
  Y4               0.500     0.4646     0.0000     0.0301     0.0013 1.000 1.000

Categorical Latent Variables

 C#1      ON
  CG#1             1.000     1.1918     0.0000     0.1402     0.0368 1.000 1.000

 Means
  CG#1             0.000     0.0520     0.0000     0.0633     0.0027 1.000 0.000
  C#1              0.000    -0.0697     0.0000     0.0910     0.0049 1.000 0.000


QUALITY OF NUMERICAL RESULTS

     Average Condition Number for the Information Matrix      0.345E-01
       (ratio of smallest to largest eigenvalue)


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 1


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


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1                 5
 Y2                 0             6
 Y3                 0             0             7
 Y4                 0             0             0             8


     PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 2


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1                  9            10            11            12


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1                 5
 Y2                 0             6
 Y3                 0             0             7
 Y4                 0             0             0             8


     PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 1


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


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1                13
 Y2                 0            14
 Y3                 0             0            15
 Y4                 0             0             0            16


     PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 2


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1                  9            10            11            12


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1                13
 Y2                 0            14
 Y3                 0             0            15
 Y4                 0             0             0            16


     PARAMETER SPECIFICATION FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS PATTERN 1 1
              G$1
              ________
 1                  0


           TAU(U) FOR LATENT CLASS PATTERN 1 2
              G$1
              ________
 1                  0


           TAU(U) FOR LATENT CLASS PATTERN 2 1
              G$1
              ________
 1                  0


           TAU(U) FOR LATENT CLASS PATTERN 2 2
              G$1
              ________
 1                  0


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              CG#1          CG#2          C#1           C#2
              ________      ________      ________      ________
 1                 17             0            18             0


           BETA(C)
              CG#1          CG#2
              ________      ________
 C#1               19             0
 C#2                0             0


     STARTING VALUES FOR LATENT CLASS PATTERN 1 1


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1             -1.000        -1.000        -1.000        -1.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.000         1.000
 Y3             0.000         0.000         1.000
 Y4             0.000         0.000         0.000         1.000


     STARTING VALUES FOR LATENT CLASS PATTERN 1 2


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1              1.000         1.000         1.000         1.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.000         1.000
 Y3             0.000         0.000         1.000
 Y4             0.000         0.000         0.000         1.000


     STARTING VALUES FOR LATENT CLASS PATTERN 2 1


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1             -1.000        -1.000        -1.000        -1.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             0.500
 Y2             0.000         0.500
 Y3             0.000         0.000         0.500
 Y4             0.000         0.000         0.000         0.500


     STARTING VALUES FOR LATENT CLASS PATTERN 2 2


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1              1.000         1.000         1.000         1.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             0.500
 Y2             0.000         0.500
 Y3             0.000         0.000         0.500
 Y4             0.000         0.000         0.000         0.500


     STARTING VALUES FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS PATTERN 1 1
              G$1
              ________
 1             15.000


           TAU(U) FOR LATENT CLASS PATTERN 1 2
              G$1
              ________
 1             15.000


           TAU(U) FOR LATENT CLASS PATTERN 2 1
              G$1
              ________
 1            -15.000


           TAU(U) FOR LATENT CLASS PATTERN 2 2
              G$1
              ________
 1            -15.000


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


           BETA(C)
              CG#1          CG#2
              ________      ________
 C#1            1.000         0.000
 C#2            0.000         0.000


     POPULATION VALUES FOR LATENT CLASS PATTERN 1 1


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1             -1.000        -1.000        -1.000        -1.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.000         1.000
 Y3             0.000         0.000         1.000
 Y4             0.000         0.000         0.000         1.000


     POPULATION VALUES FOR LATENT CLASS PATTERN 1 2


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1              1.000         1.000         1.000         1.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.000         1.000
 Y3             0.000         0.000         1.000
 Y4             0.000         0.000         0.000         1.000


     POPULATION VALUES FOR LATENT CLASS PATTERN 2 1


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1             -1.000        -1.000        -1.000        -1.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             0.500
 Y2             0.000         0.500
 Y3             0.000         0.000         0.500
 Y4             0.000         0.000         0.000         0.500


     POPULATION VALUES FOR LATENT CLASS PATTERN 2 2


           NU
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 1              1.000         1.000         1.000         1.000


           THETA
              Y1            Y2            Y3            Y4
              ________      ________      ________      ________
 Y1             0.500
 Y2             0.000         0.500
 Y3             0.000         0.000         0.500
 Y4             0.000         0.000         0.000         0.500


     POPULATION VALUES FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS PATTERN 1 1
              G$1
              ________
 1             15.000


           TAU(U) FOR LATENT CLASS PATTERN 1 2
              G$1
              ________
 1             15.000


           TAU(U) FOR LATENT CLASS PATTERN 2 1
              G$1
              ________
 1            -15.000


           TAU(U) FOR LATENT CLASS PATTERN 2 2
              G$1
              ________
 1            -15.000


     POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


           BETA(C)
              CG#1          CG#2
              ________      ________
 C#1            1.000         0.000
 C#2            0.000         0.000


TECHNICAL 8 OUTPUT


  TECHNICAL 8 OUTPUT FOR REPLICATION 1


  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE      CLASS COUNTS    ALGORITHM
     1 -0.62849684D+04    0.0000000    0.0000000    387.168   125.832    EM
                                                    234.990   252.010
     2 -0.62738425D+04   11.1259400    0.0017702    387.008   125.992    EM
                                                    235.014   251.986
     3 -0.62738300D+04    0.0124337    0.0000020    387.000   126.000    EM
                                                    235.022   251.978
     4 -0.62738299D+04    0.0001678    0.0000000    386.998   126.002    EM
                                                    235.023   251.977
     5 -0.62738299D+04    0.0000028    0.0000000    386.998   126.002    EM
                                                    235.023   251.977
     6 -0.62738299D+04    0.0000001    0.0000000    386.998   126.002    EM
                                                    235.023   251.977


SAVEDATA INFORMATION

  Order of variables

    G
    Y1
    Y2
    Y3
    Y4
    CG
    C

  Save file
    ex7.21.dat

  Save file format           Free
  Save file record length    10000


     Beginning Time:  22:03:06
        Ending Time:  22:03:06
       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