Mplus VERSION 6
MUTHEN & MUTHEN
04/25/2010  11:25 PM

INPUT INSTRUCTIONS

  title: jasab.inp

  montecarlo:
      names are y1 y2 y3 x;
      nobs = 2000;
      nreps = 500;
      seed = 578243;
      classes = c(3);
      genclasses = c(3);
      cutpoints = x(0);

  analysis:
      type = mixture;

  model montecarlo:
      %overall%
      [x@0]; x@1;

      i by y1-y3@1;
      s by y1@0 y2@1 y3@2;
      [y1-y3@0 i*0 s*1];
      i*6.25; ! SD = 2.5
      s*1;
      !total s variance is 1.25 (1/5 of i variance),  SD = 1.12
      i with s*.699; !this gives correlation 0.25
      y1*2.083 y2*0.417 y3 *.417; !this gives y1 and y2 r-square 0.75
      ! y1 variance = 8.333, SD = 2.89
      ! y2 variance = 9.135, SD = 3.052
      ! within-group y2 variance = 9.135 - 0.25 = 9.065, SD = 3.01

      s on x*1;
      !this gives ES = 0.33 in y2 within-group SD terms (for medium class)
      !r-squared for s is 20%

      [c#1*-1.9459 c#2*-1.2528];

      %c#1% !low class (10%)
      [i*0.0 s*.75];
      !low class grows at 1/4 SD per grade
      !low class is lower by 1 SD for intercept,
      !about 1.5 SD lower for slope
      s on x*0.25;

      %c#2% ! high class (20%)
      [i*5.0 s*2.25];
      !high class grows at 3/4 SD per grade
      s on x*.25;
      ! high class has 1/4 effect of low class, ES = 0.08

      %c#3% !medium class (70%)
      [i*2.5 s*2.25];
      !medium class grows at 3/4 SD per grade
      !low class is lower by 1 SD for intercept,
      !about 1.5 SD lower for slope




  model:
      %overall%


      i by y1-y3@1;
      s by y1@0 y2@1 y3@2;
      [y1-y3@0 i*0 s*1];
      i*6.25; ! SD = 2.5
      s*1;
      !total s variance is 1.25 (1/5 of i variance),  SD = 1.12
      i with s*.699; !this gives correlation 0.25
      y1*2.083 y2*0.417 y3 *.417; !this gives y1 and y2 r-square 0.75
      ! y1 variance = 8.333, SD = 2.89
      ! y2 variance = 9.135, SD = 3.052
      ! within-group y2 variance = 9.135 - 0.25 = 9.065, SD = 3.01

      s on x*1;
      !this gives ES = 0.33 in y2 within-group SD terms (for medium class)
      !r-squared for s is 20%

      [c#1*-1.9459 c#2*-1.2528];

      %c#1% !low class (10%)
      [i*0.0 s*.75];
      !low class grows at 1/4 SD per grade
      !low class is lower by 1 SD for intercept,
      !about 1.5 SD lower for slope
      s on x*0.25;

      %c#2% ! high class (20%)
      [i*5.0 s*2.25];
      !high class grows at 3/4 SD per grade
      s on x*.25;
      ! high class has 1/4 effect of low class, ES = 0.08

      %c#3% !medium class (70%)
      [i*2.5 s*2.25];
      !medium class grows at 3/4 SD per grade
      !low class is lower by 1 SD for intercept,
      !about 1.5 SD lower for slope




  output:
      sampstat tech9;



*** WARNING in OUTPUT command
  SAMPSTAT option is the default for MONTECARLO.
   1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS



jasab.inp

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        2000

Number of replications
    Requested                                                  500
    Completed                                                  500
Value of seed                                               578243

Number of dependent variables                                    3
Number of independent variables                                  1
Number of continuous latent variables                            2
Number of categorical latent variables                           1

Observed dependent variables

  Continuous
   Y1          Y2          Y3

Observed independent variables
   X

Continuous latent variables
   I           S

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


SAMPLE STATISTICS FOR THE FIRST REPLICATION


     SAMPLE STATISTICS


           Means
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1              2.716         5.221         7.741         0.501


           Covariances
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1            10.374
 Y2             9.373        12.330
 Y3            10.588        14.595        19.110
 X              0.017         0.235         0.422         0.250


           Correlations
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1             1.000
 Y2             0.829         1.000
 Y3             0.752         0.951         1.000
 X              0.011         0.134         0.193         1.000




TESTS OF MODEL FIT

Number of Free Parameters                       17

Loglikelihood

    H0 Value

        Mean                            -12694.911
        Std Dev                             54.494
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.992       -12821.681     -12819.615
           0.980       0.988       -12806.826     -12800.511
           0.950       0.956       -12784.549     -12779.514
           0.900       0.908       -12764.751     -12763.184
           0.800       0.784       -12740.774     -12744.027
           0.700       0.692       -12723.488     -12724.559
           0.500       0.478       -12694.911     -12697.354
           0.300       0.286       -12666.335     -12667.846
           0.200       0.200       -12649.049     -12650.044
           0.100       0.108       -12625.072     -12620.331
           0.050       0.054       -12605.274     -12602.827
           0.020       0.030       -12582.997     -12574.438
           0.010       0.016       -12568.142     -12563.020

Information Criteria

    Akaike (AIC)

        Mean                             25423.823
        Std Dev                            108.988
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.984        25170.284      25152.296
           0.980       0.970        25199.994      25181.820
           0.950       0.946        25244.549      25235.684
           0.900       0.892        25284.144      25271.737
           0.800       0.800        25332.099      25330.633
           0.700       0.714        25366.670      25369.586
           0.500       0.522        25423.823      25428.672
           0.300       0.308        25480.976      25483.092
           0.200       0.216        25515.547      25521.021
           0.100       0.092        25563.502      25559.132
           0.050       0.044        25603.097      25585.040
           0.020       0.012        25647.651      25624.358
           0.010       0.008        25677.361      25664.597

    Bayesian (BIC)

        Mean                             25519.038
        Std Dev                            108.988
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.984        25265.500      25247.512
           0.980       0.970        25295.210      25277.035
           0.950       0.946        25339.764      25330.900
           0.900       0.892        25379.359      25366.952
           0.800       0.800        25427.314      25425.848
           0.700       0.714        25461.885      25464.801
           0.500       0.522        25519.038      25523.888
           0.300       0.308        25576.191      25578.308
           0.200       0.216        25610.762      25616.236
           0.100       0.092        25658.717      25654.348
           0.050       0.044        25698.312      25680.255
           0.020       0.012        25742.867      25719.573
           0.010       0.008        25772.577      25759.812

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

        Mean                             25465.028
        Std Dev                            108.988
        Number of successful computations      500

             Proportions                   Percentiles
        Expected    Observed         Expected       Observed
           0.990       0.984        25211.490      25193.502
           0.980       0.970        25241.200      25223.025
           0.950       0.946        25285.754      25276.890
           0.900       0.892        25325.349      25312.942
           0.800       0.800        25373.304      25371.838
           0.700       0.714        25407.875      25410.791
           0.500       0.522        25465.028      25469.878
           0.300       0.308        25522.182      25524.298
           0.200       0.216        25556.752      25562.226
           0.100       0.092        25604.707      25600.338
           0.050       0.044        25644.302      25626.245
           0.020       0.012        25688.857      25665.563
           0.010       0.008        25718.567      25705.803



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

    Latent
   Classes

       1        202.95151          0.10148
       2        495.83800          0.24792
       3       1301.21049          0.65061


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

    Latent
   Classes

       1        202.95152          0.10148
       2        495.83799          0.24792
       3       1301.21049          0.65061


CLASSIFICATION QUALITY

     Entropy                         0.441


CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP

Class Counts and Proportions

    Latent
   Classes

       1              133          0.06675
       2              396          0.19791
       3             1471          0.73535


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

           1        2        3

    1   0.704    0.075    0.221
    2   0.037    0.665    0.298
    3   0.063    0.163    0.774


MODEL RESULTS

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

 I        BY
  Y1               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000

 S        BY
  Y1               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               2.000     2.0000     0.0000     0.0000     0.0000 1.000 0.000

 S          ON
  X                0.250     0.2261     0.3942     0.3395     0.1557 0.932 0.190

 I        WITH
  S                0.699     0.6900     0.2466     0.2305     0.0608 0.862 0.850

 Means
  I                0.000    -0.1154     0.5855     0.5771     0.3554 0.908 0.092

 Intercepts
  Y1               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  S                0.750     0.7364     0.3653     0.3215     0.1334 0.940 0.676

 Variances
  I                6.250     6.0463     0.8096     0.7358     0.6957 0.824 0.994

 Residual Variances
  Y1               2.083     2.0738     0.1484     0.1517     0.0221 0.948 1.000
  Y2               0.417     0.4215     0.0748     0.0783     0.0056 0.962 1.000
  Y3               0.417     0.4116     0.1808     0.1908     0.0327 0.958 0.566
  S                1.000     0.9430     0.1512     0.1555     0.0261 0.928 0.994

Latent Class 2

 I        BY
  Y1               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000

 S        BY
  Y1               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               2.000     2.0000     0.0000     0.0000     0.0000 1.000 0.000

 S          ON
  X                0.250     0.1234     0.7024     0.4750     0.5084 0.772 0.394

 I        WITH
  S                0.699     0.6900     0.2466     0.2305     0.0608 0.862 0.850

 Means
  I                5.000     5.1837     1.2638     0.8943     1.6278 0.826 0.976

 Intercepts
  Y1               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  S                2.250     2.3161     0.5347     0.3808     0.2897 0.810 0.972

 Variances
  I                6.250     6.0463     0.8096     0.7358     0.6957 0.824 0.994

 Residual Variances
  Y1               2.083     2.0738     0.1484     0.1517     0.0221 0.948 1.000
  Y2               0.417     0.4215     0.0748     0.0783     0.0056 0.962 1.000
  Y3               0.417     0.4116     0.1808     0.1908     0.0327 0.958 0.566
  S                1.000     0.9430     0.1512     0.1555     0.0261 0.928 0.994

Latent Class 3

 I        BY
  Y1               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000

 S        BY
  Y1               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               1.000     1.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               2.000     2.0000     0.0000     0.0000     0.0000 1.000 0.000

 S          ON
  X                1.000     1.0613     0.2997     0.1815     0.0934 0.896 0.978

 I        WITH
  S                0.699     0.6900     0.2466     0.2305     0.0608 0.862 0.850

 Means
  I                2.500     2.4099     0.4233     0.3782     0.1870 0.786 0.962

 Intercepts
  Y1               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y2               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  Y3               0.000     0.0000     0.0000     0.0000     0.0000 1.000 0.000
  S                2.250     2.2487     0.2412     0.1750     0.0581 0.854 0.992

 Variances
  I                6.250     6.0463     0.8096     0.7358     0.6957 0.824 0.994

 Residual Variances
  Y1               2.083     2.0738     0.1484     0.1517     0.0221 0.948 1.000
  Y2               0.417     0.4215     0.0748     0.0783     0.0056 0.962 1.000
  Y3               0.417     0.4116     0.1808     0.1908     0.0327 0.958 0.566
  S                1.000     0.9430     0.1512     0.1555     0.0261 0.928 0.994

Categorical Latent Variables

 Means
  C#1             -1.946    -1.8771     0.4755     0.4753     0.2304 0.934 0.928
  C#2             -1.253    -1.2269     1.1996     0.8853     1.4369 0.768 0.382


QUALITY OF NUMERICAL RESULTS

     Average Condition Number for the Information Matrix      0.827E-03
       (ratio of smallest to largest eigenvalue)


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION FOR LATENT CLASS 1


           NU
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1                  0             0             0             0


           LAMBDA
              I             S             X
              ________      ________      ________
 Y1                 0             0             0
 Y2                 0             0             0
 Y3                 0             0             0
 X                  0             0             0


           THETA
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1                 1
 Y2                 0             2
 Y3                 0             0             3
 X                  0             0             0             0


           ALPHA
              I             S             X
              ________      ________      ________
 1                  4             5             0


           BETA
              I             S             X
              ________      ________      ________
 I                  0             0             0
 S                  0             0             6
 X                  0             0             0


           PSI
              I             S             X
              ________      ________      ________
 I                  7
 S                  8             9
 X                  0             0             0


     PARAMETER SPECIFICATION FOR LATENT CLASS 2


           NU
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1                  0             0             0             0


           LAMBDA
              I             S             X
              ________      ________      ________
 Y1                 0             0             0
 Y2                 0             0             0
 Y3                 0             0             0
 X                  0             0             0


           THETA
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1                 1
 Y2                 0             2
 Y3                 0             0             3
 X                  0             0             0             0


           ALPHA
              I             S             X
              ________      ________      ________
 1                 10            11             0


           BETA
              I             S             X
              ________      ________      ________
 I                  0             0             0
 S                  0             0            12
 X                  0             0             0


           PSI
              I             S             X
              ________      ________      ________
 I                  7
 S                  8             9
 X                  0             0             0


     PARAMETER SPECIFICATION FOR LATENT CLASS 3


           NU
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1                  0             0             0             0


           LAMBDA
              I             S             X
              ________      ________      ________
 Y1                 0             0             0
 Y2                 0             0             0
 Y3                 0             0             0
 X                  0             0             0


           THETA
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1                 1
 Y2                 0             2
 Y3                 0             0             3
 X                  0             0             0             0


           ALPHA
              I             S             X
              ________      ________      ________
 1                 13            14             0


           BETA
              I             S             X
              ________      ________      ________
 I                  0             0             0
 S                  0             0            15
 X                  0             0             0


           PSI
              I             S             X
              ________      ________      ________
 I                  7
 S                  8             9
 X                  0             0             0


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2           C#3
              ________      ________      ________
 1                 16            17             0


           GAMMA(C)
              X
              ________
 C#1                0
 C#2                0
 C#3                0


     STARTING VALUES FOR LATENT CLASS 1


           NU
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1              0.000         0.000         0.000         0.000


           LAMBDA
              I             S             X
              ________      ________      ________
 Y1             1.000         0.000         0.000
 Y2             1.000         1.000         0.000
 Y3             1.000         2.000         0.000
 X              0.000         0.000         1.000


           THETA
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1             2.083
 Y2             0.000         0.417
 Y3             0.000         0.000         0.417
 X              0.000         0.000         0.000         0.000


           ALPHA
              I             S             X
              ________      ________      ________
 1              0.000         0.750         0.000


           BETA
              I             S             X
              ________      ________      ________
 I              0.000         0.000         0.000
 S              0.000         0.000         0.250
 X              0.000         0.000         0.000


           PSI
              I             S             X
              ________      ________      ________
 I              6.250
 S              0.699         1.000
 X              0.000         0.000         0.500


     STARTING VALUES FOR LATENT CLASS 2


           NU
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1              0.000         0.000         0.000         0.000


           LAMBDA
              I             S             X
              ________      ________      ________
 Y1             1.000         0.000         0.000
 Y2             1.000         1.000         0.000
 Y3             1.000         2.000         0.000
 X              0.000         0.000         1.000


           THETA
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1             2.083
 Y2             0.000         0.417
 Y3             0.000         0.000         0.417
 X              0.000         0.000         0.000         0.000


           ALPHA
              I             S             X
              ________      ________      ________
 1              5.000         2.250         0.000


           BETA
              I             S             X
              ________      ________      ________
 I              0.000         0.000         0.000
 S              0.000         0.000         0.250
 X              0.000         0.000         0.000


           PSI
              I             S             X
              ________      ________      ________
 I              6.250
 S              0.699         1.000
 X              0.000         0.000         0.500


     STARTING VALUES FOR LATENT CLASS 3


           NU
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1              0.000         0.000         0.000         0.000


           LAMBDA
              I             S             X
              ________      ________      ________
 Y1             1.000         0.000         0.000
 Y2             1.000         1.000         0.000
 Y3             1.000         2.000         0.000
 X              0.000         0.000         1.000


           THETA
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1             2.083
 Y2             0.000         0.417
 Y3             0.000         0.000         0.417
 X              0.000         0.000         0.000         0.000


           ALPHA
              I             S             X
              ________      ________      ________
 1              2.500         2.250         0.000


           BETA
              I             S             X
              ________      ________      ________
 I              0.000         0.000         0.000
 S              0.000         0.000         1.000
 X              0.000         0.000         0.000


           PSI
              I             S             X
              ________      ________      ________
 I              6.250
 S              0.699         1.000
 X              0.000         0.000         0.500


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2           C#3
              ________      ________      ________
 1             -1.946        -1.253         0.000


           GAMMA(C)
              X
              ________
 C#1            0.000
 C#2            0.000
 C#3            0.000


     POPULATION VALUES FOR LATENT CLASS 1


           NU
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1              0.000         0.000         0.000         0.000


           LAMBDA
              I             S             X
              ________      ________      ________
 Y1             1.000         0.000         0.000
 Y2             1.000         1.000         0.000
 Y3             1.000         2.000         0.000
 X              0.000         0.000         1.000


           THETA
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1             2.083
 Y2             0.000         0.417
 Y3             0.000         0.000         0.417
 X              0.000         0.000         0.000         0.000


           ALPHA
              I             S             X
              ________      ________      ________
 1              0.000         0.750         0.000


           BETA
              I             S             X
              ________      ________      ________
 I              0.000         0.000         0.000
 S              0.000         0.000         0.250
 X              0.000         0.000         0.000


           PSI
              I             S             X
              ________      ________      ________
 I              6.250
 S              0.699         1.000
 X              0.000         0.000         1.000


     POPULATION VALUES FOR LATENT CLASS 2


           NU
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1              0.000         0.000         0.000         0.000


           LAMBDA
              I             S             X
              ________      ________      ________
 Y1             1.000         0.000         0.000
 Y2             1.000         1.000         0.000
 Y3             1.000         2.000         0.000
 X              0.000         0.000         1.000


           THETA
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1             2.083
 Y2             0.000         0.417
 Y3             0.000         0.000         0.417
 X              0.000         0.000         0.000         0.000


           ALPHA
              I             S             X
              ________      ________      ________
 1              5.000         2.250         0.000


           BETA
              I             S             X
              ________      ________      ________
 I              0.000         0.000         0.000
 S              0.000         0.000         0.250
 X              0.000         0.000         0.000


           PSI
              I             S             X
              ________      ________      ________
 I              6.250
 S              0.699         1.000
 X              0.000         0.000         1.000


     POPULATION VALUES FOR LATENT CLASS 3


           NU
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 1              0.000         0.000         0.000         0.000


           LAMBDA
              I             S             X
              ________      ________      ________
 Y1             1.000         0.000         0.000
 Y2             1.000         1.000         0.000
 Y3             1.000         2.000         0.000
 X              0.000         0.000         1.000


           THETA
              Y1            Y2            Y3            X
              ________      ________      ________      ________
 Y1             2.083
 Y2             0.000         0.417
 Y3             0.000         0.000         0.417
 X              0.000         0.000         0.000         0.000


           ALPHA
              I             S             X
              ________      ________      ________
 1              2.500         2.250         0.000


           BETA
              I             S             X
              ________      ________      ________
 I              0.000         0.000         0.000
 S              0.000         0.000         1.000
 X              0.000         0.000         0.000


           PSI
              I             S             X
              ________      ________      ________
 I              6.250
 S              0.699         1.000
 X              0.000         0.000         1.000


     POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2           C#3
              ________      ________      ________
 1             -1.946        -1.253         0.000


           GAMMA(C)
              X
              ________
 C#1            0.000
 C#2            0.000
 C#3            0.000


TECHNICAL 9 OUTPUT

  Error messages for each replication (if any)


     REPLICATION 48:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 1 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 48:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 2 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 48:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 3 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 186:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 1 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 186:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 2 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 186:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 3 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 236:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 1 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 236:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 2 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 236:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 3 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 248:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 1 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 248:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 2 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 248:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 3 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 271:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 1 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 271:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 2 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 271:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 3 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 358:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 1 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 358:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 2 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 358:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 3 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 361:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 1 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 361:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 2 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.


     REPLICATION 361:
     WARNING:  THE RESIDUAL COVARIANCE MATRIX (THETA)  IN CLASS 3 IS NOT
     POSITIVE DEFINITE.  THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL
     VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE
     BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO
     OBSERVED VARIABLES.  CHECK THE RESULTS SECTION FOR MORE INFORMATION.
     PROBLEM INVOLVING VARIABLE Y3.



     Beginning Time:  23:25:58
        Ending Time:  23:28:16
       Elapsed Time:  00:02:18



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