TITLE:
  Parallel model
DATA:
  FILE IS myData.csv;
VARIABLE:
  NAMES ARE X1-X6;
MODEL:
  TASKGOAL BY X1* X2-X6 (lambda);
  TASKGOAL@1;  
  X1-X6 (theta);
OUTPUT:
  STDYX;


TITLE:
  Tau-equivalent model
DATA:
  FILE IS myData.csv;
VARIABLE:
  NAMES ARE X1-X6;
MODEL:
  TASKGOAL BY X1* X2-X6 (lambda);
  TASKGOAL@1;  
  X1-X6;
OUTPUT:
  STDYX;


TITLE:
  Congeneric model
DATA:
  FILE IS myData.csv;
VARIABLE:
  NAMES ARE X1-X6;
MODEL:
  TASKGOAL BY X1* X2-X6;
  TASKGOAL@1;  
  X1-X6;
OUTPUT:
  STDYX;


TITLE:
  Congeneric model, with omega estimate
DATA:
  FILE IS myData.csv;
VARIABLE:
  NAMES ARE X1-X6;
ANALYSIS:
  BOOTSTRAP IS 5000;
MODEL:
  TASKGOAL BY X1* (L1) 
              X2 (L2)
              X3 (L3)
              X4 (L4)
              X5 (L5)
              X6 (L6);
  TASKGOAL@1;  
  X1 (TH1);
  X2 (TH2);
  X3 (TH3);
  X4 (TH4);
  X5 (TH5);
  X6 (TH6);
MODEL CONSTRAINT:
  NEW(sumL sumth omega);
  L1 > 0;
  L2 > 0;
  L3 > 0;
  L4 > 0;
  L5 > 0;
  L6 > 0;
  sumL = L1 + L2 + L3 + L4 + L5 + L6;
  sumTH = TH1 + TH2 + TH3 + TH4 + TH5 + TH6;
  omega = ((sumL)^2)/(((sumL)^2)+sumTH);
OUTPUT:
  STDYX; CINT(bcbootstrap);
