Mplus VERSION 8
MUTHEN & MUTHEN
04/10/2017   3:40 AM

INPUT INSTRUCTIONS

  Title: analyzing the ex9.30step1 data
          which has missing data.
          Not using Tinterval
          analyzing/saving not missing observations
          by commenting out missing= and using Useobs
          and not using Lagged so that y&1 is not saved

  Data:
      file = ex9.30step1.dat;

  Variable:
      names = u z y w time subject;
      ! don't read y-lag because then all records have missing
      usev = z y w;
   !   missing = all(999);
      cluster = subject;
      between = z w;
   !   lagged = y(1);
  !    Tinterval = time(1);
      useobs = y ne 999;

      auxiliary = time;

  ANALYSIS:
      TYPE = twolevel RANDOM;
        		estimator=bayes;
              proc=2;
                biter=(1000);

  MODEL: ! just apply a simple model:

      %WITHIN%
      y;

      %BETWEEN%
      y on w;
      z on y;

  Output:
        tech1 tech8;

  Plot:
      type = plot3;

  Savedata: ! this will be the "real data":
      file = ex9.30.dat;



*** WARNING in MODEL command
  TYPE=RANDOM is used to declare random effect variables in the model.
  No random effect variables were found.  TYPE=RANDOM will be ignored.
   1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS



analyzing the ex9.30step1 data
which has missing data.
Not using Tinterval
analyzing/saving not missing observations
by commenting out missing= and using Useobs
and not using Lagged so that y&1 is not saved

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        9994

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

Observed dependent variables

  Continuous
   Z           Y

Observed independent variables
   W

Observed auxiliary variables
   TIME

Variables with special functions

  Cluster variable      SUBJECT

  Between variables
   Z           W


Estimator                                                    BAYES
Specifications for Bayesian Estimation
  Point estimate                                            MEDIAN
  Number of Markov chain Monte Carlo (MCMC) chains               2
  Random seed for the first chain                                0
  Starting value information                           UNPERTURBED
  Treatment of categorical mediator                         LATENT
  Algorithm used for Markov chain Monte Carlo           GIBBS(PX1)
  Convergence criterion                                  0.500D-01
  Maximum number of iterations                               50000
  K-th iteration used for thinning                               1

Input data file(s)
  ex9.30step1.dat
Input data format  FREE


SUMMARY OF DATA

     Number of clusters                        200

       Size (s)    Cluster ID with Size s

         38        187
         39        165 27
         41        83 159
         42        13 14 172 118
         43        115 61 181 25
         44        126 128 73 160 18 109 28 16
         45        148 153 110 81 68 92 175 41 132 188 197
         46        20 84 86 23 46 173 133 139 54 151 152
         47        10 140 96 101 103 106 69 72 48 34 125 56 176 57 184
                   130 85 190 11 200
         48        138 167 121 124 143 43 149 29 12 63 82 5 164
         49        114 49 90 40 141 122 31 33 4 186 127 47 156 194 195
                   67 199 35
         50        62 21 150 8 39 182 30 185 6 157 42 78 15 44 146 169
                   171
         51        50 154 93 66 97 3 162 74 75 166 191 107 108 196 36 198
                   80 113
         52        89 116 26 189 136 91 76 123 52 94 53 22 98
         53        180 155 17 102 65 32 131 24 100
         54        144 145 99 163 147 77 59 135 60 170 38 105 55 58 142
                   179 120
         55        193 19 177 111 2 1 9 168
         56        104 161 119 183 88 79 129 37 70 64
         57        112 71 178 95 158 7
         58        137 117
         59        45 87
         60        51 134
         61        174 192




UNIVARIATE SAMPLE STATISTICS


     UNIVARIATE HIGHER-ORDER MOMENT DESCRIPTIVE STATISTICS

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

     Z                     0.179      -0.024      -0.903    0.50%      -0.213      0.021      0.197
             200.000       0.187      -0.463       1.255    0.50%       0.318      0.576
     Y                    -0.040       0.344      -3.981    0.01%      -1.020     -0.373     -0.091
            9994.000       1.395       0.674       5.630    0.01%       0.199      0.878
     W                    -0.067       0.070      -2.681    0.50%      -1.046     -0.386     -0.059
             200.000       1.094      -0.509       2.781    0.50%       0.307      0.862


THE MODEL ESTIMATION TERMINATED NORMALLY

     USE THE FBITERATIONS OPTION TO INCREASE THE NUMBER OF ITERATIONS BY A FACTOR
     OF AT LEAST TWO TO CHECK CONVERGENCE AND THAT THE PSR VALUE DOES NOT INCREASE.



MODEL FIT INFORMATION

Number of Free Parameters                               7

Bayesian Posterior Predictive Checking using Chi-Square

          95% Confidence Interval for the Difference Between
          the Observed and the Replicated Chi-Square Values

                                 24.107            59.972

          Posterior Predictive P-Value              0.000

Information Criteria

          Deviance (DIC)                        30354.545
          Estimated Number of Parameters (pD)     169.342



MODEL RESULTS

                                Posterior  One-Tailed         95% C.I.
                    Estimate       S.D.      P-Value   Lower 2.5%  Upper 2.5%  Significance

Within Level

 Variances
    Y                  1.197       0.017      0.000       1.164       1.234      *

Between Level

 Y          ON
    W                  0.308       0.024      0.000       0.264       0.358      *

 Z          ON
    Y                  0.793       0.047      0.000       0.698       0.882      *

 Intercepts
    Z                  0.210       0.020      0.000       0.172       0.252      *
    Y                 -0.019       0.025      0.219      -0.068       0.027

 Residual Variances
    Z                  0.065       0.008      0.000       0.051       0.084      *
    Y                  0.096       0.013      0.000       0.074       0.125      *


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION FOR WITHIN


           NU
              Y
              ________
                    0


           LAMBDA
              Y
              ________
 Y                  0


           THETA
              Y
              ________
 Y                  0


           ALPHA
              Y
              ________
                    0


           BETA
              Y
              ________
 Y                  0


           PSI
              Y
              ________
 Y                  1


     PARAMETER SPECIFICATION FOR BETWEEN


           NU
              Z             Y             W
              ________      ________      ________
                    0             0             0


           LAMBDA
              Z             Y             W
              ________      ________      ________
 Z                  0             0             0
 Y                  0             0             0
 W                  0             0             0


           THETA
              Z             Y             W
              ________      ________      ________
 Z                  0
 Y                  0             0
 W                  0             0             0


           ALPHA
              Z             Y             W
              ________      ________      ________
                    2             3             0


           BETA
              Z             Y             W
              ________      ________      ________
 Z                  0             4             0
 Y                  0             0             5
 W                  0             0             0


           PSI
              Z             Y             W
              ________      ________      ________
 Z                  6
 Y                  0             7
 W                  0             0             0


     STARTING VALUES FOR WITHIN


           NU
              Y
              ________
                0.000


           LAMBDA
              Y
              ________
 Y              1.000


           THETA
              Y
              ________
 Y              0.000


           ALPHA
              Y
              ________
                0.000


           BETA
              Y
              ________
 Y              0.000


           PSI
              Y
              ________
 Y              0.698


     STARTING VALUES FOR BETWEEN


           NU
              Z             Y             W
              ________      ________      ________
                0.000         0.000         0.000


           LAMBDA
              Z             Y             W
              ________      ________      ________
 Z              1.000         0.000         0.000
 Y              0.000         1.000         0.000
 W              0.000         0.000         1.000


           THETA
              Z             Y             W
              ________      ________      ________
 Z              0.000
 Y              0.000         0.000
 W              0.000         0.000         0.000


           ALPHA
              Z             Y             W
              ________      ________      ________
                0.175        -0.040         0.000


           BETA
              Z             Y             W
              ________      ________      ________
 Z              0.000         0.000         0.000
 Y              0.000         0.000         0.000
 W              0.000         0.000         0.000


           PSI
              Z             Y             W
              ________      ________      ________
 Z              0.093
 Y              0.000         0.698
 W              0.000         0.000         0.548



     PRIORS FOR ALL PARAMETERS            PRIOR MEAN      PRIOR VARIANCE     PRIOR STD. DEV.

     Parameter 1~IG(-1.000,0.000)          infinity            infinity            infinity
     Parameter 2~N(0.000,infinity)           0.0000            infinity            infinity
     Parameter 3~N(0.000,infinity)           0.0000            infinity            infinity
     Parameter 4~N(0.000,infinity)           0.0000            infinity            infinity
     Parameter 5~N(0.000,infinity)           0.0000            infinity            infinity
     Parameter 6~IG(-1.000,0.000)          infinity            infinity            infinity
     Parameter 7~IG(-1.000,0.000)          infinity            infinity            infinity


TECHNICAL 8 OUTPUT



     Kolmogorov-Smirnov comparing posterior distributions across chains 1 and 2 using 100 draws.





     Parameter   KS Statistic P-value
     Parameter 4    0.0500    0.9995
     Parameter 1    0.0300    1.0000
     Parameter 2    0.0100    1.0000
     Parameter 5    0.0100    1.0000
     Parameter 3    0.0100    1.0000
     Parameter 7    0.0000    1.0000
     Parameter 6    0.0000    1.0000



     Simulated prior distributions

     Parameter       Prior Mean  Prior Variance  Prior Std. Dev.


     Parameter 1 Improper Prior
     Parameter 2 Improper Prior
     Parameter 3 Improper Prior
     Parameter 4 Improper Prior
     Parameter 5 Improper Prior
     Parameter 6 Improper Prior
     Parameter 7 Improper Prior


   TECHNICAL 8 OUTPUT FOR BAYES ESTIMATION

     CHAIN    BSEED
     1        0
     2        285380

                     POTENTIAL       PARAMETER WITH
     ITERATION    SCALE REDUCTION      HIGHEST PSR
     100              1.009               7
     200              1.017               2
     300              1.002               5
     400              1.006               2
     500              1.014               2
     600              1.016               2
     700              1.008               2
     800              1.013               7
     900              1.006               7
     1000             1.008               7


PLOT INFORMATION

The following plots are available:

  Histograms (sample values)
  Scatterplots (sample values)
  Between-level histograms (sample values, sample means/variances)
  Between-level scatterplots (sample values, sample means/variances)
  Bayesian posterior parameter distributions
  Bayesian posterior parameter trace plots
  Bayesian autocorrelation plots
  Bayesian posterior predictive checking scatterplots
  Bayesian posterior predictive checking distribution plots

SAVEDATA INFORMATION


  Save file
    ex9.30.dat

  Order and format of variables

    Z              F10.3
    Y              F10.3
    W              F10.3
    TIME           F10.3
    SUBJECT        I4

  Save file format
    4F10.3 I4

  Save file record length    10000


     Beginning Time:  03:40:52
        Ending Time:  03:40:53
       Elapsed Time:  00:00:01



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