Specialty of SEM Latent variables Measurement error Theory testing Multivariate statistical analysis Controlling for the errors due to statistical decision-making 3
Applications of SEM Confirmatory factor analysis (M 1) Path analysis (M 2) Structural regression analysis (M 3) Time-dependent/longitudinal data (M 4) Recursive and non-recursive models for cross-sectional data Covariance structure models Multi-sample analysis Multi-level analysis 6
Four Basic Model of SEM I CFA model 7
Four Basic Model of SEM II Path Analysis model 8
Four Basic Model of SEM III Structural Regression model 9
Four Basic Model of SEM IV Latent Change model 10
Procedures of SEM 12
Modeling of SEM Basic elements: 觀察變項(observed variable) or 測量變項(measured variable) 潛在變項(latent variable) Model specification Effects Direct effect Indirect effect Total effect 測量模式(measurement model) 指實際觀察值與其背後的潛在特質的相互關係 結構模式(structural model) 顯示潛在變項之間的關係 17
LISREL語法 1. TITLE Latent variable Path Model 2. DATA NI=6 NO=289 3. CM SY FI=groupall. cov 4. LA; out 1 out 2 out 3 co 1 co 2 co 3 5. MODEL NY=3 NE=1 NK=1 NX=3 PS=DI, FR GA=FU, FI 6. LE; 員 績效 7. LK; 組織承諾 8. FREE LX(2, 1) LX(3, 1) LY(2, 1) LY(3, 1) GA(1, 1) 9. VALUE 1 LX(1, 1) LY(1, 1) 10. PD 11. OUTPUT SE TV RS AM FS EF SS SC MI 18
SIMPLIS語法 1. Latent variable Path Model 2. Observed variables: out 1 out 2 out 3 co 1 co 2 co 3 3. Covariance Matrix from file groupall. cov 4. Sample size: 289 5. Latent variables: perform comm 6. Relationships: 7. out 1= 1*perform 8. out 2= perform 9. out 3= perform 10. co 1= 1*comm 11. co 2= comm 12. co 3= comm 13. Paths: 14. Comm -> perform 15. Path Diagram 16. LISREL OUTPUT SE TV RS AM FS EF SS SC MI 19