Msam07, Albert Satorra 1 Examples with Coupon data (Bagozzi, 1994)

Msam07, Albert Satorra 2 Data from Bagozzi, Baumgartner, and Yi (1992), on “coupon usage”. Sample A: Action oriented women (n = 85) Intentions # Intentions # Behavior Attitudes # Attitudes # Attitudes # Sample B: State oriented women (n = 64) Intentions # Intentions # Behavior Attitudes # Attitudes # Attitudes #

Msam07, Albert Satorra 3 Variables /LABELS V1 = Intentions1; V2 = Intentions2; V3 = Behavior; V4 = Attitudes1; V5 = Attitudes2; V6 = Attitudes3;

Msam07, Albert Satorra 4 V4V1 E1 Simple linear regression

Msam07, Albert Satorra 5 /TITLE Regresión lineal simple (path2.txt) /SPECIFICATIONS VARIABLES = 6; CASES = 85; METHODS=ML; MATRIX=COVARIANCE; /LABELS V1 = Intentions1; V2 = Intentions2; V3 = Behavior; V4 = Attitudes1; V5 = Attitudes2; V6 = Attitudes3; /EQUATIONS V1 = *V4 + E1; /VARIANCES V4 = *; E1 = *; /COVARIANCES /MATRIX /PRINT /LMTEST /WTEST /END Simple linear regression

Msam07, Albert Satorra 6 Simple linear regression GOODNESS OF FIT SUMMARY CHI-SQUARE = BASED ON 0 DEGREES OF FREEDOM MEASUREMENT EQUATIONS WITH STANDARD ERRORS AND TEST STATISTICS INTENTIO=V1 =.760*V E VARIANCES OF INDEPENDENT VARIABLES V F V4 -ATTITUDE 1.914*I I.295 I I I I I I E D E1 -INTENTIO 3.284*I I.507 I I I I I I STANDARDIZED SOLUTION: R-SQUARED INTENTIO=V1 =.502*V E1.252

Msam07, Albert Satorra 7 V4V1 V3 E1 Bivariate regression E3

Msam07, Albert Satorra 8 /TITLE Regresión bivariada (path3.txt) /SPECIFICATIONS VARIABLES = 6; CASES = 85; METHODS=ML; MATRIX=COVARIANCE; /LABELS V1 = Intentions1; V2 = Intentions2; V3 = Behavior; V4 = Attitudes1; V5 = Attitudes2; V6 = Attitudes3; /EQUATIONS V1 = *V4 + E1; V3 = *V4 + E3; /VARIANCES V4 = *; E3 = *; E1 = *; /COVARIANCES /MATRIX /PRINT /LMTEST /WTEST /END Bivariate regression

Msam07, Albert Satorra 9 Bivariate regression GOODNESS OF FIT SUMMARY INDEPENDENCE MODEL CHI-SQUARE = ON 3 DEGREES OF FREEDOM INDEPENDENCE AIC = INDEPENDENCE CAIC = MODEL AIC = MODEL CAIC = CHI-SQUARE = BASED ON 1 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS LESS THAN THE NORMAL THEORY RLS CHI-SQUARE FOR THIS ML SOLUTION IS BENTLER-BONETT NORMED FIT INDEX= BENTLER-BONETT NONNORMED FIT INDEX= COMPARATIVE FIT INDEX (CFI) = 0.673

Msam07, Albert Satorra 10 MEASUREMENT EQUATIONS WITH STANDARD ERRORS AND TEST STATISTICS INTENTIO=V1 =.760*V E BEHAVIOR=V3 =.517*V E VARIANCES OF INDEPENDENT VARIABLES V F V4 -ATTITUDE 1.914*I I.295 I I I I I I E D E1 -INTENTIO 3.284*I I.507 I I I I I I E3 -BEHAVIOR 1.874*I I.289 I I I I I I STANDARDIZED SOLUTION: R-SQUARED INTENTIO=V1 =.502*V E1.252 BEHAVIOR=V3 =.463*V E3.214 Bivariate regression

Msam07, Albert Satorra 11 V4V1 V3 E1 E3 Bivariate regression (correlated disturbance)

Msam07, Albert Satorra 12 Bivariate regression (correlated disturbances) /TITLE Regresión bivariada (path4.txt) /SPECIFICATIONS VARIABLES = 6; CASES = 85; METHODS=ML; MATRIX=COVARIANCE; /LABELS V1 = Intentions1; V2 = Intentions2; V3 = Behavior; V4 = Attitudes1; V5 = Attitudes2; V6 = Attitudes3; /EQUATIONS V1 = *V4 + E1; V3 = *V4 + E3; /VARIANCES V4 = *; E1 = *; E3 = *; /COVARIANCES E1,E3 = *; /MATRIX /PRINT /LMTEST /WTEST /END

Msam07, Albert Satorra 13 GOODNESS OF FIT SUMMARY CHI-SQUARE = BASED ON 0 DEGREES OF FREEDOM NONPOSITIVE DEGREES OF FREEDOM. PROBABILITY COMPUTATIONS ARE UNDEFINED. MEASUREMENT EQUATIONS WITH STANDARD ERRORS AND TEST STATISTICS INTENTIO=V1 =.760*V E BEHAVIOR=V3 =.517*V E VARIANCES OF INDEPENDENT VARIABLES V F V4 -ATTITUDE 1.914*I I.295 I I I I I I E D E1 -INTENTIO 3.284*I I.507 I I I I I I E3 -BEHAVIOR 1.874*I I.289 I I I I I I Bivariate regression (correlated disturbance)

Msam07, Albert Satorra 14 Bivariate regression (correlated disturbance) COVARIANCES AMONG INDEPENDENT VARIABLES E D E3 -BEHAVIOR 1.184*I I E1 -INTENTIO.300 I I I I I I STANDARDIZED SOLUTION: R-SQUARED INTENTIO=V1 =.502*V E1.252 BEHAVIOR=V3 =.463*V E3.214 CORRELATIONS AMONG INDEPENDENT VARIABLES E D E3 -BEHAVIOR.477*I I E1 -INTENTIO I I I I

Msam07, Albert Satorra 15 V4V1 V3 E1 E3 Simultaneous equations

Msam07, Albert Satorra 16 /TITLE Path analysis (path1.txt) /SPECIFICATIONS VARIABLES = 6; CASES = 85; METHODS=ML; MATRIX=COVARIANCE; /LABELS V1 = Intentions1; V2 = Intentions2; V3 = Behavior; V4 = Attitudes1; V5 = Attitudes2; V6 = Attitudes3; /EQUATIONS V1 = *V4 + E1; V3 = *V1 + *V4 + E3; /VARIANCES V4 = *; E1 = *; E3 = *; /COVARIANCES /MATRIX /LMTEST /WTEST /END Simultaneous equations

Msam07, Albert Satorra 17 Simultaneous equations GOODNESS OF FIT SUMMARY INDEPENDENCE MODEL CHI-SQUARE = ON 3 DEGREES OF FREEDOM INDEPENDENCE AIC = INDEPENDENCE CAIC = MODEL AIC = MODEL CAIC = CHI-SQUARE = BASED ON 0 DEGREES OF FREEDOM NONPOSITIVE DEGREES OF FREEDOM. PROBABILITY COMPUTATIONS ARE UNDEFINED. BENTLER-BONETT NORMED FIT INDEX= 1.000

Msam07, Albert Satorra 18 Simultaneous equations MEASUREMENT EQUATIONS WITH STANDARD ERRORS AND TEST STATISTICS V1 =V1 =.760*V E V3 =V3 =.360*V *V E VARIANCES OF INDEPENDENT VARIABLES V F V4 - V *I I.295 I I I I I I

Msam07, Albert Satorra 19 VARIANCES OF INDEPENDENT VARIABLES E D E1 - V *I I.507 I I I I I I E3 - V *I I.223 I I I I I I STANDARDIZED SOLUTION: R-SQUARED V1 =V1 =.502*V E1.252 V3 =V3 =.489*V *V E3.393 Simultaneous equations

Msam07, Albert Satorra 20 F1 V1 V3 E1 E3 V4 V5 V6 E4 E5 E6 SEM multiple indicators

Msam07, Albert Satorra 21 SEM: Action oriented /TITLE SEM indicadores múltiples (Lisrel1.txt) /SPECIFICATIONS VARIABLES = 6; CASES = 85; METHODS=ML; MATRIX=COVARIANCE; /LABELS V1 = Intentions1; V2 = Intentions2; V3 = Behavior; V4 = Attitudes1; V5 = Attitudes2; V6 = Attitudes3; /EQUATIONS V4 = *F1 + E4; V5 = *F1 + E5; V6 = *F1 + E6; V1 = *F1 + E1; V3 = *F1 + *V1 + E3; /VARIANCES F1 = 1; E1 = *; E3 TO E6 = *; /COVARIANCES /MATRIX /LMTEST /WTEST /END

Msam07, Albert Satorra 22 F1F2 V3 D2 E3 SEM multiple indicators V4 V5 V6 V1 V2 E4 E5 E6 E1 E2

Msam07, Albert Satorra 23 /TITLE Path analysis /SPECIFICATIONS VARIABLES = 6; CASES = 85; METHODS=ML; MATRIX=COVARIANCE; ! GROUPS = 2; /LABELS V1 = Inte1; V2 = Inten2; V3 = Beha; V4 = Att1; V5 = Att2; V6 = Att3; F1 = Att; F2 = Int; /EQUATIONS V4 = *F1 + E4; V5 = *F1 + E5; V6 = *F1 + E6; V1 = 1F2 + E1; V2 = *F2 + E2; F2 = *F1 + D2; V3 = *F1 + *F2 + E3; /VARIANCES F1 = 1; D2 =* ; E1 T0 E6 = *; /COVARIANCES /MATRIX /PRINT !/LMTEST !/WTEST /END SEM: Action oriented

Msam07, Albert Satorra 24 INTE1 =V1 = F E1 INTEN2 =V2 = 1.014*F E2.088 BEHA =V3 =.330*F *F E ATT1 =V4 = 1.020*F E4.136 ATT2 =V5 =.951*F E5.117 ATT3 =V6 = 1.269*F E6.127 SEM: Action oriented INTE1 =V1 =.923 F E1.852 INTEN2 =V2 =.934*F E2.872 BEHA =V3 =.413*F *F E3.450 ATT1 =V4 =.737*F E4.543 ATT2 =V5 =.781*F E5.611 ATT3 =V6 =.904*F E6.817 INT =F2 =.678*F D2.460 GOODNESS OF FIT SUMMARY FOR METHOD = ML CHI-SQUARE = BASED ON 7 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS.60809

Msam07, Albert Satorra 25 SEM: State oriented /TITLE Path analysis /SPECIFICATIONS VARIABLES = 6; CASES = 64; METHODS=ML; MATRIX=COVARIANCE; /LABELS V1 = Inte1; V2 = Inten2; V3 = Beha; V4 = Att1; V5 = Att2; V6 = Att3; F1 = Att; F2 = Int; /EQUATIONS V4 = *F1 + E4; V5 = *F1 + E5; V6 = *F1 + E6; V1 = 1F2 + E1; V2 = *F2 + E2; F2 = *F1 + D2; V3 = *F1 + *F2 + E3; /VARIANCES F1 = 1; D2 =* ; E1 =*; E2 =*; E3 T0 E6 = *; /COVARIANCES !E3,E2=*; /MATRIX /PRINT /LMTEST ! PROCESS =SIMULTANEOUS; ! SET=PVV,PFV,PFF,PDD,PEE; /WTEST /END GOODNESS OF FIT SUMMARY FOR METHOD = ML CHI-SQUARE = BASED ON 7 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS.14722

Msam07, Albert Satorra 26 SEM: multiple group /TITLE state ortiented /SPECIFICATIONS VARIABLES = 6; CASES = 64; METHODS=ML; MATRIX=COVARIANCE; /LABELS V1 = Inte1; V2 = Inten2; V3 = Beha; V4 = Att1; V5 = Att2; V6 = Att3; F1 = Att; F2 = Int; /EQUATIONS V4 = *F1 + E4; V5 = *F1 + E5; V6 = *F1 + E6; V1 = 1F2 + E1; V2 = *F2 + E2; F2 = *F1 + D2; V3 = *F1 + *F2 + E3; /VARIANCES F1 = 1; D2 =* ; E1 T0 E6 = *; /COVARIANCES E3,E2=*; /MATRIX /PRINT /LMTEST PROCESS =SIMULTANEOUS; SET=PVV,PFV,PFF,PDD,PEE; /WTEST /END /TITLE Action oriented /SPECIFICATIONS VARIABLES = 6; CASES = 85; METHODS=ML; MATRIX=COVARIANCE; GROUPS = 2; /LABELS V1 = Inte1; V2 = Inten2; V3 = Beha; V4 = Att1; V5 = Att2; V6 = Att3; F1 = Att; F2 = Int; /EQUATIONS V4 = *F1 + E4; V5 = *F1 + E5; V6 = *F1 + E6; V1 = 1F2 + E1; V2 = *F2 + E2; F2 = *F1 + D2; V3 = *F1 + *F2 + E3; /VARIANCES F1 = 1; D2 =* ; E1 T0 E6 = *; /COVARIANCES /MATRIX !/PRINT !/LMTEST !/WTEST /END GOODNESS OF FIT SUMMARY FOR METHOD = ML INDEPENDENCE MODEL CHI-SQUARE = ON 30 DEGREES OF FREEDOM CHI-SQUARE = BASED ON 13 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS.25757

Msam07, Albert Satorra 27 /TITLE Action oriented /SPECIFICATIONS VARIABLES = 6; CASES = 85; METHODS=ML; MATRIX=COVARIANCE; GROUPS = 2; /LABELS V1 = Inte1; V2 = Inten2; V3 = Beha; V4 = Att1; V5 = Att2; V6 = Att3; F1 = Att; F2 = Int; /EQUATIONS V4 = *F1 + E4; V5 = *F1 + E5; V6 = *F1 + E6; V1 = 1F2 + E1; V2 = *F2 + E2; F2 = *F1 + D2; V3 = *F1 + *F2 + E3; /VARIANCES F1 = 1; D2 =* ; E1 T0 E6 = *; /COVARIANCES /MATRIX !/PRINT !/LMTEST !/WTEST /END SEM: multiple group /TITLE state ortiented /SPECIFICATIONS VARIABLES = 6; CASES = 64; METHODS=ML; MATRIX=COVARIANCE; /LABELS V1 = Inte1; V2 = Inten2; V3 = Beha; V4 = Att1; V5 = Att2; V6 = Att3; F1 = Att; F2 = Int; /EQUATIONS V4 = *F1 + E4; V5 = *F1 + E5; V6 = *F1 + E6; V1 = 1F2 + E1; V2 = *F2 + E2; F2 = *F1 + D2; V3 = *F1 + *F2 + E3; /VARIANCES F1 = 1; D2 =* ; E1 T0 E6 = *; /COVARIANCES E3,E2=*; /MATRIX /PRINT /LMTEST PROCESS =SIMULTANEOUS; SET=PVV,PFV,PFF,PDD,PEE; /WTEST /CONSTRAINTS (1,F2,F1) = (2,F2,F1); (1,V3,F1) = (2,V3,F1); (1,V3,F2) = (2,V3,F2); /END GOODNESS OF FIT SUMMARY FOR METHOD = ML CHI-SQUARE = BASED ON 16 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS.33206