! ! Interaction with multiple group approach ! ! Data from MacKenzie and Spreng (1992) How does motivation moderate ! the impact of central and peripheral processing on brand attitudes and ! intentions. Journal of Computer Research 18:519-529 ! ! See also Rigdon, E et al (1998) A comparative review of interaction and ! nonlinear modeling In: R. Schumacker and G. Marcoulides (eds) Interaction ! and nonlinear effects in structural equation modeling. New York: Erlbaum ! ! define number of factors and number of observed variables #define nvar 6 #define nfac 2 Title interaction for Ad & Brand attitude: Low Group Data NInput=nvar Nobs=200 NGroups=2 CMatrix Full File=low.cov Means File=low.mean Matrices A Full nfac 1 ! Factor Means D Diag nfac nfac Free ! Factor Variances B Sdiag nfac nfac Free ! Factor -> Factor paths I Iden nfac nfac L Full nvar nfac ! Factor -> Observed paths E Diag nvar nvar Free ! Residual Vars on Observed M Full nvar 1 Free ! Score Means End Matrices Start 1 L 1 1 L 4 2 Free L 2 1 L 3 1 L 5 2 L 6 2 Mean L*(I-B)~*A + M ; Covariance L*(I-B)~*D*(I-B)~'*L'+ E ; Option RS End Group Title interaction for Ad & Brand attitude: High Group Data NInput=nvar Nobs=160 NGroups=2 CMatrix Full File=high.cov Means File=high.mean Matrices = Group 1 A Full nfac 1 Free ! Factor Means (different from group 1) B Sdiag nfac nfac Free ! Factor -> Factor paths (different from group 1) End Matrices Start 1 All Mean L*(I-B)~*A + M ; Covariance L*(I-B)~*D*(I-B)~'*L'+ E ; Option Rsid Option Multiple End Group ! write current results to binary file Save general.mxs ! Fit model with same slopes Equate B 1 2 1 B 2 2 1 End ! Fit model with same means Get general.mxs Drop 20 21 !Equate A 2 1 1 A 1 1 1 !Equate A 2 2 1 A 1 2 1 End ! Fit model with same means and same slopes Equate B 1 2 1 B 2 2 1 End