Example Mx Script

! Mx ACE script for twin data

#define nvar 3

Group1: Defines Matrices
Data Calc NGroups=4

	Begin Matrices;
		X Lower nvar nvar free    ! genetic structure
		Y Lower nvar nvar free    ! shared environment 
		Z Lower nvar nvar free    ! non-shared environment
	
		H Full 1 1
		I Iden 4 4 
	End Matrices;

	Matrix H .5

	Begin Algebra;
		A= X*X';   ! genetic covariance matrix
		C= Y*Y';   ! environmental covariance matrix
		E= Z*Z';   ! nonshared environmental covariance matrix
	End Algebra;

	Start 0   X 1 1 to X nvar nvar 	
	Start 0   Y 1 1 to Y nvar nvar
	Start 1.7 Z 1 1 to Z nvar nvar

End


Group2: MZ twin pairs
Data NInput_vars=6 NObservations=1500
     CMatrix 
     4.24756
     -.280441  3.39532
     2.01213    .05206    2.95854
     3.2865    -.243047   2.01504   4.39321
     -.210246  2.38388     .096846  -.202754  3.42946
     2.02091    .050704   2.44859   2.02949    .114946  2.86705

     Labels x1 y1 z1 x2 y2 z2 

     Matrices= Group 1

     Covariances A + C + E  |    A + C  _
                   A + C    |  A + C + E /

     Option RS
End


Group3: DZ twin pairs
Data NInput_vars=6 NObservations=2000
     CMatrix 
     4.35496
     -.354591  3.68418
     2.04503    .097915  3.17886
     2.12497    .329648  1.41837   4.15677
      .241837  1.64101    .430632  -.216949  3.43144
     1.34426    .501343  1.70592   2.01647    .139561   3.12658


     Labels x1 y1 z1 x2 y2 z2 

     Matrices= Group 1

     Covariances A + C + E  |   H@A + C  _
                  H@A + C   |  A + C + E /

     Option RS
End



Group4: Standardised solution
Calculation

	Matrices = group 1
	
	Begin Algebra;

	  ! phenotypic covariance matrix  
	  P = A + C + E;

	  ! diagonal matrix of phenotypic 
	  ! standard deviations
	  D = \sqrt(\v2d(\d2v(P)));

	  ! phenotypically standardised genetic 
	  !  covariance matrix
	  T = D~ * A * D~;

	  ! phenotypically standardised shared 
	  !  environmental covariance matrix
	  U = D~ * C * D~;

	  ! phenotypically standardised 
	  !  nonshared environmental covariance matrix
	  V = D~ * E * D~;

	  ! Genetic correlation matrix
	  G = \stnd(T);

	  ! Shared environmental correlation matrix
	  S = \stnd(U);

	  ! Nonshared environmental correlation matrix
	  N = \stnd(V);


	End Algebra;

End