! Measurement part subject variables is used ! Analysis controls for stratification ! Number of subjects in largest family: 2 ! Number of subject variables: 2 ! Number of indicators for subject variables: 5 ! Number of dummy variables for genotypes: 2 ! Number of dummy variables for family types: 5 Group 1: General part subject variables Calculation ng=4 Matrices a Full 2 1 Fixed ! Means subject variables; Alpha B Full 2 2 Fixed ! Causal effects subject variables on each other; Beta P Symm 2 2 Fixed ! Residual (co)variances subject variables; Psi(y) v Full 5 1 Free ! Intercepts subject indicators; Nu(y) L Full 5 2 Fixed ! Factor loadings subject indicators; Lamda(y) T Symm 5 5 Fixed ! Measurement errors subject indicators; Theta(y) C Symm 5 5 Free ! Covariances between family members; C End Matrices Free B 2 1 Free P 1 1 P 2 2 Free L 4 2 L 5 2 Free T 1 1 T 2 2 T 3 3 T 4 4 T 5 5 Matrix a ! specify (starting) values for (free) parameters 0.0 0.0 Matrix B ! (starting) values: Main diagonal B should ALWAYS remain zero 0 0.0 0.3 0 Matrix P ! (starting) values 1.0 0.0 1.0 Matrix v ! (starting) values 0.0 0.0 0.0 0.0 0.0 Matrix L ! (starting) values 1.0 0.0 1.0 0.0 0.0 1.0 0.0 0.9 0.0 0.9 Matrix T ! (starting) values 0.6 0.0 0.6 0.0 0.0 0.6 0.0 0.0 0.0 0.6 0.0 0.0 0.0 0.0 0.6 Matrix C ! starting values 0.3 0.1 0.3 0.1 0.1 0.3 0.1 0.1 0.1 0.3 0.1 0.1 0.1 0.1 0.3 Output Group 2: Genetic effects Calculation Matrices N Full 5 2 Fixed ! Intercepts; Nu = 2 stacked 5 x 1 subvectors End Matrices Free N 3 1 to N 5 2 Output Group 3: Stratification effects on subject variables Calculation Matrices N Full 5 5 Fixed ! Intercepts; Nu(y) = 5 stacked 5 x 1 subvectors End Matrices Free N 3 1 to N 5 5 Output Group 4: Fit model to data Data NInput=19 Rectangular File=example.dat Labels F1 F2 F3 F4 F5 Y1_1 Y2_1 Y3_1 Y4_1 Y5_1 G1_1 G2_1 Y1_2 Y2_2 Y3_2 Y4_2 Y5_2 G1_2 G2_2 Definition F1 F2 F3 F4 F5 G1_1 G2_1 G1_2 G2_2 / Matrices a Full 2 1 =a1 b Full 2 2 =B1 c Symm 2 2 =P1 d Full 5 1 =v1 e Full 5 2 =N2 f Full 5 5 =N3 g Full 5 2 =L1 h Symm 5 5 =T1 i Symm 5 5 =C1 j Iden 2 2 ! identity matrix subject variables k Full 5 1 ! family type dummy variables l Full 2 1 ! genetic dummy variables subject 1 m Full 2 1 ! genetic dummy variables subject 2 End Matrices Means (d+e*l+f*k) + (g)*(j-(b))~*(a) _ ! mean subject 1 (d+e*m+f*k) + (g)*(j-(b))~*(a) / ! mean subject 2 Covariances (g)*(j-(b))~*(c)*((j-(b))~)'*(g)' + (h) | (i) _ ! variance subject 1 (i) | (g)*(j-(b))~*(c)*((j-(b))~)'*(g)' + (h) / ! variance subject 2 Specify k F1 F2 F3 F4 F5 Specify l G1_1 G2_1 Specify m G1_2 G2_2 Option Multiple Issat End Save indpath.mxs ! Test for genetic effects on N Fix N 2 3 1 to N 2 5 2 Value 0 N 2 3 1 to N 2 5 2 End Get indpath.mxs ! Test for statification effects on N Fix N 3 3 1 to N 3 5 5 Value 0 N 3 3 1 to N 3 5 5 End Get indpath.mxs ! Test for statification + genetic effects on N Fix N 2 3 1 to N 2 5 2 Value 0 N 2 3 1 to N 2 5 2 Fix N 3 3 1 to N 3 5 5 Value 0 N 3 3 1 to N 3 5 5 End