! This is example script for k=3 trait test

#DEFINE total 6                        ! define the variable "total"
#NGROUPS 3

G1: PARAMETER ESTIMATES                ! parameter specification 
CALCULATION

BEGIN MATRICES;
A FULL 1 1 FREE                        ! A is free parameter whith dimension 1 by 1                  
B FULL 1 1 FREE
C FULL 1 1 FREE
X FULL total total FIXED               ! X is 6 by 6 matrix with fixed values assigned in the following lines
END MATRICES;                          ! (This is submatrix of inverted Fisher information matrixthat correspond to six parameter of interests

Value 7.710474640438282 X 1 1          ! Assign the value to each element of X from the calculated submatrix of inverted Fisher information
Value 7.709260663212016 X 2 2
Value 7.711691774397430 X 3 3           
Value 4.663702915655440 X 4 4
Value 4.620667030846704 X 5 5
Value 4.679200672505286 X 6 6
Value 1.617538218457437 X 1 2 X 2 1
Value 1.530250893440179 X 1 3 X 3 1
Value 3.546715188981548 X 1 4 X 4 1
Value -3.449854515258192 X 1 5 X 5 1
Value -1.573289443908528 X 1 6 X 6 1
Value 1.647925282478313 X 2 3 X 3 2
Value 3.546421968829633 X 2 4 X 4 2
Value -1.632671504988344 X 2 5 X 5 2
Value -3.578418676335090 X 2 6 X 6 2
Value 1.588011722661225 X 3 4 X 4 3
Value -3.450140420881972 X 3 5 X 5 3
Value -3.579009967331238 X 3 6 X 6 3
Value -2.576001700429044 X 4 5 X 5 4
Value -2.541120409739163 X 4 6 X 6 4
Value 2.567510428234816 X 5 6 X 6 5

BEGIN ALGEBRA;                        ! Then specify the constraints among the parameters of intersts (theta1, theta2,..., theta6)
H=A*A;                                ! This is theta 1
I=B*B;                                ! This is theta 2
J=C*C;                                ! This is theta 3
M=A*B;                                ! This is theta 4
N=A*C;                                ! This is theta 5
Q=B*C;                                ! This is theta 6 
END ALGEBRA;                          
END

G2: MLE
DATA NINPUT=6 NOBSERBATIONS=1        ! Read the data file "myData2.dat", which has one observation Z, which has 6 columns and one row.  
RECTANGULAR FILE=myData2.dat
LABELS X1 X2 X3 X4 X5 X6
BEGIN MATRICES = GROUP 1;
MEANS H_I_J_M_N_Q;                   ! this form mean parameters of Z
COVARIANCES X;                       ! X is covariance of Z, but since we fixed the values in X, it will not estimate the covariance.
START 1 ALL;                         ! Starting values for all parameters
OPTION NDECIMALS=9                   ! decimal places
!DROP 1 2 3                          ! Use this script twice both for the full model and the null model. When you estimate the null model remove "!" 
END                                  ! sign at the beginig of this line, then it will drop parameter A, B, C. If you estimate the full model, keep "!" sign
                                     ! then it won't drop any parameters and thus estimate the full model

G3: GET FUNCTION                     ! This is to get the maximum likelihood function value 
CALCULATION
BEGIN MATRICES;
Z FULL 1 1 = %F2
END MATRICES;
END

! to run this scirpt in unix, use the command "mx < myscript.mx > output.FULL.mxo"   (output.FULL.mxo can be any output file name)
! Note you also need input data file, "myData2.dat" to run this script