title: imputing missing on X.  
    using information from U, X and Y.

data:
    file = stageA.dat;

variable:
    names = u1-u12 x1-x3 y1-y3 w1-w9 cp1-cp9 n1 n2 mlcjoint;
    usev = n1 n2 x1-x3 y1-y3;
    categorical = y1 y2;
    nominal = n1 n2;
    missing = *; 
    classes = c1(3) c2(3);
 

data imputation:
    names = u1-u12(C) x1(c) x2 x3 y1(c) y2(c) y3;
    impute = x1(c) x2;
    ndatasets = 100;
    save = imputed*.dat;
    thin = 100;

analysis:
    type = mixture;
    estimator = mlr;
    starts = 0;

model:
    %overall%
    c2 on c1;
    c1-c2 on x1-x3;
    y1-y3 on x1-x3;
    
MODEL C1:

       %C1#1%

       [n1#1@2.607 n1#2@0.558];

       %C1#2%

       [n1#1@0.042 n1#2@2.294];

       %C1#3%

       [n1#1@-4.165 n1#2@-2.120];


    Model C2:


    %C2#1%
     [n2#1@2.575 n2#2@0.497];

    [y1$1 y2$1 y2$2 y3];

    %C2#2%

    [n2#1@0.155 n2#2@2.308];

    [y1$1 y2$1 y2$2 y3];


    %C2#3%

     [n2#1@-4.205 n2#2@-2.172];

    [y1$1 y2$1 y2$2 y3];


   
output:
    standardized cinterval;
