Mplus VERSION 7.3
MUTHEN & MUTHEN
09/22/2014   5:18 PM

INPUT INSTRUCTIONS

  title:
  	this is an example of mixture randomized
  	trials modeling using CACE estimation with
  	missing data on the latent class indicator

  montecarlo:
  	names are u y x1 x2;
  	generate = u(1);
  	categorical = u;
  	! u is compliance status: 0/1 for noncomplying/complying
  	! u is a perfect indicator of c
  	missing = u;
  	cutpoints = x2(0);
  	! x2 is the 0/1 ctrl/tx dummy. Here split 50/50
  	genclasses = c(2);
  	classes = c(2);
  	nobs = 500;
  	seed = 3454367;
  	nrep = 1;
  	save = ex7.24.dat;

  analysis:
  	type = mixture;

  model population:

  	%overall%

  	x1-x2*1;
  	[x1-x2*0];


  	[c#1*0];

  	c#1 on x1*1;

  	y on x1*2 x2*.5;
  	
  	[y*1]; y*1;
  	
  	%c#1% !noncompliers

  	[u$1@15]; ! P(u = 1) = 0

  	y on x2@0;
  	[y*2];
  	y*2;

  	%c#2% !compliers

  	[u$1@-15]; ! P(u = 1) = 1

  	y on x2*.5;
  	[y*3];
  	y*1;

  model missing:

  	%overall%

  	! the ctrl/tx dummy x2 determines u missingness
  	! note: model missing uses logistic regression
  	! parameterization with intercept and slope

  	[u@15]; ! prob missing = 1 for ctrls (x2=0)
  	u on x2@-30; ! prob missing = 0 for tx (x2=1)

  model:

  	%overall%


  	[c#1*0];

  	c#1 on x1*1;

  	y on x1*2 x2*.5;
  	
  	[y*1]; y*1;
  	
  	%c#1% !noncompliers

  	[u$1@15]; ! P(u = 1 | c=1) = 0

  	y on x2@0;
  	[y*2];
  	y*2;

  	%c#2% !compliers

  	[u$1@-15]; ! P(u = 1 | c=2) = 1

  	y on x2*.5;
  	[y*3];
  	y*1;


  output:
  	tech8 tech9;	



INPUT READING TERMINATED NORMALLY




this is an example of mixture randomized
trials modeling using CACE estimation with
missing data on the latent class indicator

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                                    2
Number of independent variables                                  2
Number of continuous latent variables                            0
Number of categorical latent variables                           1

Observed dependent variables

  Continuous
   Y

  Binary and ordered categorical (ordinal)
   U

Observed independent variables
   X1          X2

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
Maximum number of iterations for H1                           2000
Convergence criterion for H1                             0.100D-03
Optimization algorithm                                         EMA
Link                                                         LOGIT


SUMMARY OF DATA FOR THE FIRST REPLICATION

     Number of missing data patterns             2
     Number of y missing data patterns           1
     Number of u missing data patterns           2


SUMMARY OF MISSING DATA PATTERNS FOR THE FIRST REPLICATION


     MISSING DATA PATTERNS (x = not missing)

           1  2
 U         x
 Y         x  x
 X1        x  x
 X2        x  x


     MISSING DATA PATTERN FREQUENCIES

    Pattern   Frequency     Pattern   Frequency
          1         247           2         253


     MISSING DATA PATTERNS FOR U (x = not missing)

           1  2
 U         x


     MISSING DATA PATTERN FREQUENCIES FOR U

    Pattern   Frequency     Pattern   Frequency
          1         247           2         253


     MISSING DATA PATTERNS FOR Y (x = not missing)

           1
 Y         x
 X1        x
 X2        x


     MISSING DATA PATTERN FREQUENCIES FOR Y

    Pattern   Frequency
          1         500


COVARIANCE COVERAGE OF DATA FOR THE FIRST REPLICATION

Minimum covariance coverage value   0.100


     PROPORTION OF DATA PRESENT


           Covariance Coverage
              U             Y             X1            X2
              ________      ________      ________      ________
 U              0.494
 Y              0.494         1.000
 X1             0.494         1.000         1.000
 X2             0.494         1.000         1.000         1.000


     PROPORTION OF DATA PRESENT FOR U


           Covariance Coverage
              U
              ________
 U              0.494


     PROPORTION OF DATA PRESENT FOR Y


           Covariance Coverage
              Y             X1            X2
              ________      ________      ________
 Y              1.000
 X1             1.000         1.000
 X2             1.000         1.000         1.000


SAMPLE STATISTICS FOR THE FIRST REPLICATION


     ESTIMATED SAMPLE STATISTICS


           Means
              Y             X1            X2
              ________      ________      ________
 1              2.519        -0.061         0.494


           Covariances
              Y             X1            X2
              ________      ________      ________
 Y              4.592
 X1             1.754         1.039
 X2             0.086        -0.026         0.250


           Correlations
              Y             X1            X2
              ________      ________      ________
 Y              1.000
 X1             0.803         1.000
 X2             0.081        -0.052         1.000


     MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -1902.367




MODEL FIT INFORMATION

Number of Free Parameters                        8

Loglikelihood

    H0 Value

        Mean                              -920.329
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         -920.329       -920.329
           0.980       0.000         -920.329       -920.329
           0.950       0.000         -920.329       -920.329
           0.900       0.000         -920.329       -920.329
           0.800       0.000         -920.329       -920.329
           0.700       0.000         -920.329       -920.329
           0.500       0.000         -920.329       -920.329
           0.300       0.000         -920.329       -920.329
           0.200       0.000         -920.329       -920.329
           0.100       0.000         -920.329       -920.329
           0.050       0.000         -920.329       -920.329
           0.020       0.000         -920.329       -920.329
           0.010       0.000         -920.329       -920.329

Information Criteria

    Akaike (AIC)

        Mean                              1856.658
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         1856.658       1856.658
           0.980       0.000         1856.658       1856.658
           0.950       0.000         1856.658       1856.658
           0.900       0.000         1856.658       1856.658
           0.800       0.000         1856.658       1856.658
           0.700       0.000         1856.658       1856.658
           0.500       0.000         1856.658       1856.658
           0.300       0.000         1856.658       1856.658
           0.200       0.000         1856.658       1856.658
           0.100       0.000         1856.658       1856.658
           0.050       0.000         1856.658       1856.658
           0.020       0.000         1856.658       1856.658
           0.010       0.000         1856.658       1856.658

    Bayesian (BIC)

        Mean                              1890.375
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         1890.375       1890.375
           0.980       0.000         1890.375       1890.375
           0.950       0.000         1890.375       1890.375
           0.900       0.000         1890.375       1890.375
           0.800       0.000         1890.375       1890.375
           0.700       0.000         1890.375       1890.375
           0.500       0.000         1890.375       1890.375
           0.300       0.000         1890.375       1890.375
           0.200       0.000         1890.375       1890.375
           0.100       0.000         1890.375       1890.375
           0.050       0.000         1890.375       1890.375
           0.020       0.000         1890.375       1890.375
           0.010       0.000         1890.375       1890.375

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

        Mean                              1864.983
        Std Dev                              0.000
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.000         1864.983       1864.983
           0.980       0.000         1864.983       1864.983
           0.950       0.000         1864.983       1864.983
           0.900       0.000         1864.983       1864.983
           0.800       0.000         1864.983       1864.983
           0.700       0.000         1864.983       1864.983
           0.500       0.000         1864.983       1864.983
           0.300       0.000         1864.983       1864.983
           0.200       0.000         1864.983       1864.983
           0.100       0.000         1864.983       1864.983
           0.050       0.000         1864.983       1864.983
           0.020       0.000         1864.983       1864.983
           0.010       0.000         1864.983       1864.983

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

    Pearson Chi-Square

        Mean                                 0.557
        Std Dev                              0.000
        Degrees of freedom                       0
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       1.000            0.000          0.557
           0.980       1.000            0.000          0.557
           0.950       1.000            0.000          0.557
           0.900       1.000            0.000          0.557
           0.800       1.000            0.000          0.557
           0.700       1.000            0.000          0.557
           0.500       1.000            0.000          0.557
           0.300       1.000            0.000          0.557
           0.200       1.000            0.000          0.557
           0.100       1.000            0.000          0.557
           0.050       1.000            0.000          0.557
           0.020       1.000            0.000          0.557
           0.010       1.000            0.000          0.557

    Likelihood Ratio Chi-Square

        Mean                                 0.558
        Std Dev                              0.000
        Degrees of freedom                       0
        Number of successful computations        1

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       1.000            0.000          0.558
           0.980       1.000            0.000          0.558
           0.950       1.000            0.000          0.558
           0.900       1.000            0.000          0.558
           0.800       1.000            0.000          0.558
           0.700       1.000            0.000          0.558
           0.500       1.000            0.000          0.558
           0.300       1.000            0.000          0.558
           0.200       1.000            0.000          0.558
           0.100       1.000            0.000          0.558
           0.050       1.000            0.000          0.558
           0.020       1.000            0.000          0.558
           0.010       1.000            0.000          0.558

Chi-Square Test for MCAR under the Unrestricted Latent Class Indicator Model

    Pearson Chi-Square for MCAR

        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



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

    Latent
   Classes

       1        230.45489          0.46091
       2        269.54511          0.53909


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

    Latent
   Classes

       1        230.45473          0.46091
       2        269.54527          0.53909


FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP

Class Counts and Proportions

    Latent
   Classes

       1              228          0.45600
       2              272          0.54400


CLASSIFICATION QUALITY

     Entropy                         0.658


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

           1        2

    1   0.881    0.119
    2   0.109    0.891


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

           1        2

    1   0.872    0.128
    2   0.101    0.899


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

              1        2

    1      1.916    0.000
    2     -2.190    0.000


MODEL RESULTS

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

 Y          ON
  X1                  2.000     1.9604     0.0000     0.0683     0.0016 1.000 1.000
  X2                  0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000

 Intercepts
  Y                   2.000     2.1227     0.0000     0.1171     0.0151 1.000 1.000

 Thresholds
  U$1                15.000    15.0000     0.0000     0.0000     0.0000 1.000 0.000

 Residual Variances
  Y                   2.000     1.9570     0.0000     0.1871     0.0018 1.000 1.000

Latent Class 2

 Y          ON
  X1                  2.000     1.9604     0.0000     0.0683     0.0016 1.000 1.000
  X2                  0.500     0.6281     0.0000     0.1504     0.0164 1.000 1.000

 Intercepts
  Y                   3.000     2.7561     0.0000     0.1407     0.0595 1.000 1.000

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

 Residual Variances
  Y                   1.000     0.9751     0.0000     0.0873     0.0006 1.000 1.000

Categorical Latent Variables

 C#1        ON
  X1                  1.000     1.5412     0.0000     0.2054     0.2929 0.000 1.000

 Intercepts
  C#1                 0.000    -0.1473     0.0000     0.1513     0.0217 1.000 0.000


QUALITY OF NUMERICAL RESULTS

     Average Condition Number for the Information Matrix      0.285E-01
       (ratio of smallest to largest eigenvalue)


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION FOR LATENT CLASS 1


           NU
              Y             X1            X2
              ________      ________      ________
 1                  0             0             0


           LAMBDA
              Y             X1            X2
              ________      ________      ________
 Y                  0             0             0
 X1                 0             0             0
 X2                 0             0             0


           THETA
              Y             X1            X2
              ________      ________      ________
 Y                  0
 X1                 0             0
 X2                 0             0             0


           ALPHA
              Y             X1            X2
              ________      ________      ________
 1                  1             0             0


           BETA
              Y             X1            X2
              ________      ________      ________
 Y                  0             2             0
 X1                 0             0             0
 X2                 0             0             0


           PSI
              Y             X1            X2
              ________      ________      ________
 Y                  3
 X1                 0             0
 X2                 0             0             0


     PARAMETER SPECIFICATION FOR LATENT CLASS 2


           NU
              Y             X1            X2
              ________      ________      ________
 1                  0             0             0


           LAMBDA
              Y             X1            X2
              ________      ________      ________
 Y                  0             0             0
 X1                 0             0             0
 X2                 0             0             0


           THETA
              Y             X1            X2
              ________      ________      ________
 Y                  0
 X1                 0             0
 X2                 0             0             0


           ALPHA
              Y             X1            X2
              ________      ________      ________
 1                  4             0             0


           BETA
              Y             X1            X2
              ________      ________      ________
 Y                  0             2             5
 X1                 0             0             0
 X2                 0             0             0


           PSI
              Y             X1            X2
              ________      ________      ________
 Y                  6
 X1                 0             0
 X2                 0             0             0


     PARAMETER SPECIFICATION FOR LATENT CLASS INDICATOR MODEL PART


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


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


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2
              ________      ________
 1                  7             0


           GAMMA(C)
              X1            X2
              ________      ________
 C#1                8             0
 C#2                0             0


     STARTING VALUES FOR LATENT CLASS 1


           NU
              Y             X1            X2
              ________      ________      ________
 1              0.000         0.000         0.000


           LAMBDA
              Y             X1            X2
              ________      ________      ________
 Y              1.000         0.000         0.000
 X1             0.000         1.000         0.000
 X2             0.000         0.000         1.000


           THETA
              Y             X1            X2
              ________      ________      ________
 Y              0.000
 X1             0.000         0.000
 X2             0.000         0.000         0.000


           ALPHA
              Y             X1            X2
              ________      ________      ________
 1              2.000         0.000         0.000


           BETA
              Y             X1            X2
              ________      ________      ________
 Y              0.000         2.000         0.000
 X1             0.000         0.000         0.000
 X2             0.000         0.000         0.000


           PSI
              Y             X1            X2
              ________      ________      ________
 Y              2.000
 X1             0.000         0.500
 X2             0.000         0.000         0.500


     STARTING VALUES FOR LATENT CLASS 2


           NU
              Y             X1            X2
              ________      ________      ________
 1              0.000         0.000         0.000


           LAMBDA
              Y             X1            X2
              ________      ________      ________
 Y              1.000         0.000         0.000
 X1             0.000         1.000         0.000
 X2             0.000         0.000         1.000


           THETA
              Y             X1            X2
              ________      ________      ________
 Y              0.000
 X1             0.000         0.000
 X2             0.000         0.000         0.000


           ALPHA
              Y             X1            X2
              ________      ________      ________
 1              3.000         0.000         0.000


           BETA
              Y             X1            X2
              ________      ________      ________
 Y              0.000         2.000         0.500
 X1             0.000         0.000         0.000
 X2             0.000         0.000         0.000


           PSI
              Y             X1            X2
              ________      ________      ________
 Y              1.000
 X1             0.000         0.500
 X2             0.000         0.000         0.500


     STARTING VALUES FOR LATENT CLASS INDICATOR MODEL PART


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


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


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


           GAMMA(C)
              X1            X2
              ________      ________
 C#1            1.000         0.000
 C#2            0.000         0.000


     POPULATION VALUES FOR LATENT CLASS 1


           NU
              Y             X1            X2
              ________      ________      ________
 1              0.000         0.000         0.000


           LAMBDA
              Y             X1            X2
              ________      ________      ________
 Y              1.000         0.000         0.000
 X1             0.000         1.000         0.000
 X2             0.000         0.000         1.000


           THETA
              Y             X1            X2
              ________      ________      ________
 Y              0.000
 X1             0.000         0.000
 X2             0.000         0.000         0.000


           ALPHA
              Y             X1            X2
              ________      ________      ________
 1              2.000         0.000         0.000


           BETA
              Y             X1            X2
              ________      ________      ________
 Y              0.000         2.000         0.000
 X1             0.000         0.000         0.000
 X2             0.000         0.000         0.000


           PSI
              Y             X1            X2
              ________      ________      ________
 Y              2.000
 X1             0.000         1.000
 X2             0.000         0.000         1.000


     POPULATION VALUES FOR LATENT CLASS 2


           NU
              Y             X1            X2
              ________      ________      ________
 1              0.000         0.000         0.000


           LAMBDA
              Y             X1            X2
              ________      ________      ________
 Y              1.000         0.000         0.000
 X1             0.000         1.000         0.000
 X2             0.000         0.000         1.000


           THETA
              Y             X1            X2
              ________      ________      ________
 Y              0.000
 X1             0.000         0.000
 X2             0.000         0.000         0.000


           ALPHA
              Y             X1            X2
              ________      ________      ________
 1              3.000         0.000         0.000


           BETA
              Y             X1            X2
              ________      ________      ________
 Y              0.000         2.000         0.500
 X1             0.000         0.000         0.000
 X2             0.000         0.000         0.000


           PSI
              Y             X1            X2
              ________      ________      ________
 Y              1.000
 X1             0.000         1.000
 X2             0.000         0.000         1.000


     POPULATION VALUES FOR LATENT CLASS INDICATOR MODEL PART


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


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


     POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART


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


           GAMMA(C)
              X1            X2
              ________      ________
 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 -0.92780823D+03    0.0000000    0.0000000    237.098   262.902    EM
     2 -0.92227007D+03    5.5381539    0.0059691    234.607   265.393    EM
     3 -0.92096124D+03    1.3088368    0.0014191    232.956   267.044    EM
     4 -0.92053160D+03    0.4296313    0.0004665    231.959   268.041    EM
     5 -0.92039501D+03    0.1365967    0.0001484    231.365   268.635    EM
     6 -0.92035141D+03    0.0435998    0.0000474    231.013   268.987    EM
     7 -0.92033701D+03    0.0143948    0.0000156    230.801   269.199    EM
     8 -0.92033202D+03    0.0049880    0.0000054    230.672   269.328    EM
     9 -0.92033021D+03    0.0018151    0.0000020    230.592   269.408    EM
    10 -0.92032952D+03    0.0006883    0.0000007    230.542   269.458    EM
    11 -0.92032925D+03    0.0002690    0.0000003    230.511   269.489    EM
    12 -0.92032914D+03    0.0001074    0.0000001    230.490   269.510    EM
    13 -0.92032910D+03    0.0000435    0.0000000    230.478   269.522    EM
    14 -0.92032908D+03    0.0000178    0.0000000    230.469   269.531    EM
    15 -0.92032908D+03    0.0000073    0.0000000    230.464   269.536    EM
    16 -0.92032907D+03    0.0000030    0.0000000    230.461   269.539    EM
    17 -0.92032907D+03    0.0000012    0.0000000    230.458   269.542    EM
    18 -0.92032907D+03    0.0000005    0.0000000    230.457   269.543    EM
    19 -0.92032907D+03    0.0000002    0.0000000    230.456   269.544    EM
    20 -0.92032907D+03    0.0000001    0.0000000    230.456   269.544    EM
    21 -0.92032907D+03    0.0000000    0.0000000    230.455   269.545    EM
    22 -0.92032907D+03    0.0000000    0.0000000    230.455   269.545    EM
    23 -0.92032907D+03    0.0000000    0.0000000    230.455   269.545    EM


TECHNICAL 9 OUTPUT

  Error messages for each replication (if any)



SAVEDATA INFORMATION

  Order of variables

    U
    Y
    X1
    X2
    C

  Save file
    ex7.24.dat

  Save file format           Free
  Save file record length    10000
  Missing designated by 999


     Beginning Time:  17:18:33
        Ending Time:  17:18:33
       Elapsed Time:  00:00:00



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