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

2. Msam07, Albert Satorra 2 Data from Bagozzi, Baumgartner, and Yi (1992), on “coupon usage”. Sample A: Action oriented women (n = 85) Intentions #14.389 Intentions #23.7924.410 Behavior1.9351.8552.385 Attitudes #11.4541.4530.9891.914 Attitudes #21.0871.3090.8410.9611.480 Attitudes #31.6231.7011.1751.2791.2201.971 Sample B: State oriented women (n = 64) Intentions #13.730 Intentions #23.2083.436 Behavior1.6871.6752.171 Attitudes #10.6210.6160.6051.373 Attitudes #21.0630.8640.4280.6711.397 Attitudes #30.8950.8180.5950.9120.6631.498

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

4. Msam07, Albert Satorra 4 V4V1 E1 Simple linear regression

5. 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 4.389 3.792 4.410 1.935 1.855 2.385 1.454 1.453 0.989 1.914 1.087 1.309 0.841 0.961 1.480 1.623 1.701 1.175 1.279 1.220 1.971 /PRINT /LMTEST /WTEST /END Simple linear regression

6. Msam07, Albert Satorra 6 Simple linear regression GOODNESS OF FIT SUMMARY CHI-SQUARE = 0.000 BASED ON 0 DEGREES OF FREEDOM MEASUREMENT EQUATIONS WITH STANDARD ERRORS AND TEST STATISTICS INTENTIO=V1 =.760*V4 +1.000 E1.143 5.315 VARIANCES OF INDEPENDENT VARIABLES ---------------------------------- V F --- --- V4 -ATTITUDE 1.914*I I.295 I I 6.481 I I I I E D --- --- E1 -INTENTIO 3.284*I I.507 I I 6.481 I I I I STANDARDIZED SOLUTION: R-SQUARED INTENTIO=V1 =.502*V4 +.865 E1.252

7. Msam07, Albert Satorra 7 V4V1 V3 E1 Bivariate regression E3

8. 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 4.389 3.792 4.410 1.935 1.855 2.385 1.454 1.453 0.989 1.914 1.087 1.309 0.841 0.961 1.480 1.623 1.701 1.175 1.279 1.220 1.971 /PRINT /LMTEST /WTEST /END Bivariate regression

9. Msam07, Albert Satorra 9 Bivariate regression GOODNESS OF FIT SUMMARY INDEPENDENCE MODEL CHI-SQUARE = 66.306 ON 3 DEGREES OF FREEDOM INDEPENDENCE AIC = 60.30569 INDEPENDENCE CAIC = 49.97773 MODEL AIC = 19.69782 MODEL CAIC = 16.25517 CHI-SQUARE = 21.698 BASED ON 1 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS LESS THAN 0.001 THE NORMAL THEORY RLS CHI-SQUARE FOR THIS ML SOLUTION IS 19.122. BENTLER-BONETT NORMED FIT INDEX= 0.673 BENTLER-BONETT NONNORMED FIT INDEX= 0.019 COMPARATIVE FIT INDEX (CFI) = 0.673

10. Msam07, Albert Satorra 10 MEASUREMENT EQUATIONS WITH STANDARD ERRORS AND TEST STATISTICS INTENTIO=V1 =.760*V4 +1.000 E1.143 5.315 BEHAVIOR=V3 =.517*V4 +1.000 E3.108 4.786 VARIANCES OF INDEPENDENT VARIABLES ---------------------------------- V F --- --- V4 -ATTITUDE 1.914*I I.295 I I 6.481 I I I I E D --- --- E1 -INTENTIO 3.284*I I.507 I I 6.481 I I I I E3 -BEHAVIOR 1.874*I I.289 I I 6.481 I I I I STANDARDIZED SOLUTION: R-SQUARED INTENTIO=V1 =.502*V4 +.865 E1.252 BEHAVIOR=V3 =.463*V4 +.886 E3.214 Bivariate regression

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

12. 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 4.389 3.792 4.410 1.935 1.855 2.385 1.454 1.453 0.989 1.914 1.087 1.309 0.841 0.961 1.480 1.623 1.701 1.175 1.279 1.220 1.971 /PRINT /LMTEST /WTEST /END

13. Msam07, Albert Satorra 13 GOODNESS OF FIT SUMMARY CHI-SQUARE = 0.000 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*V4 +1.000 E1.143 5.315 BEHAVIOR=V3 =.517*V4 +1.000 E3.108 4.786 VARIANCES OF INDEPENDENT VARIABLES ---------------------------------- V F --- --- V4 -ATTITUDE 1.914*I I.295 I I 6.481 I I I I E D --- --- E1 -INTENTIO 3.284*I I.507 I I 6.481 I I I I E3 -BEHAVIOR 1.874*I I.289 I I 6.481 I I I I Bivariate regression (correlated disturbance)

14. 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 3.947 I I I I STANDARDIZED SOLUTION: R-SQUARED INTENTIO=V1 =.502*V4 +.865 E1.252 BEHAVIOR=V3 =.463*V4 +.886 E3.214 CORRELATIONS AMONG INDEPENDENT VARIABLES --------------------------------------- E D --- --- E3 -BEHAVIOR.477*I I E1 -INTENTIO I I I I

15. Msam07, Albert Satorra 15 V4V1 V3 E1 E3 Simultaneous equations

16. 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 4.389 3.792 4.410 1.935 1.855 2.385 1.454 1.453 0.989 1.914 1.087 1.309 0.841 0.961 1.480 1.623 1.701 1.175 1.279 1.220 1.971 /LMTEST /WTEST /END Simultaneous equations

17. Msam07, Albert Satorra 17 Simultaneous equations GOODNESS OF FIT SUMMARY INDEPENDENCE MODEL CHI-SQUARE = 66.306 ON 3 DEGREES OF FREEDOM INDEPENDENCE AIC = 60.30569 INDEPENDENCE CAIC = 49.97773 MODEL AIC = 0.00000 MODEL CAIC = 0.00000 CHI-SQUARE = 0.000 BASED ON 0 DEGREES OF FREEDOM NONPOSITIVE DEGREES OF FREEDOM. PROBABILITY COMPUTATIONS ARE UNDEFINED. BENTLER-BONETT NORMED FIT INDEX= 1.000

18. Msam07, Albert Satorra 18 Simultaneous equations MEASUREMENT EQUATIONS WITH STANDARD ERRORS AND TEST STATISTICS V1 =V1 =.760*V4 +1.000 E1.143 5.315 V3 =V3 =.360*V1 +.243*V4 +1.000 E3.072.110 4.976 2.215 VARIANCES OF INDEPENDENT VARIABLES ---------------------------------- V F --- --- V4 - V4 1.914*I I.295 I I 6.481 I I I I

19. Msam07, Albert Satorra 19 VARIANCES OF INDEPENDENT VARIABLES ---------------------------------- E D --- --- E1 - V1 3.284*I I.507 I I 6.481 I I I I E3 - V3 1.447*I I.223 I I 6.481 I I I I STANDARDIZED SOLUTION: R-SQUARED V1 =V1 =.502*V4 +.865 E1.252 V3 =V3 =.489*V1 +.218*V4 +.779 E3.393 Simultaneous equations

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

21. 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 4.389 3.792 4.410 1.935 1.855 2.385 1.454 1.453 0.989 1.914 1.087 1.309 0.841 0.961 1.480 1.623 1.701 1.175 1.279 1.220 1.971 /LMTEST /WTEST /END

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

23. 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 4.389 3.792 4.410 1.935 1.855 2.385 1.454 1.453 0.989 1.914 1.087 1.309 0.841 0.961 1.480 1.623 1.701 1.175 1.279 1.220 1.971 /PRINT !/LMTEST !/WTEST /END SEM: Action oriented

24. Msam07, Albert Satorra 24 INTE1 =V1 = 1.000 F2 + 1.000 E1 INTEN2 =V2 = 1.014*F2 + 1.000 E2.088 11.585@ BEHA =V3 =.330*F2 +.492*F1 + 1.000 E3.103.204 3.203@ 2.411@ ATT1 =V4 = 1.020*F1 + 1.000 E4.136 7.501@ ATT2 =V5 =.951*F1 + 1.000 E5.117 8.124@ ATT3 =V6 = 1.269*F1 + 1.000 E6.127 10.005@ SEM: Action oriented INTE1 =V1 =.923 F2 +.384 E1.852 INTEN2 =V2 =.934*F2 +.358 E2.872 BEHA =V3 =.413*F2 +.318*F1 +.742 E3.450 ATT1 =V4 =.737*F1 +.676 E4.543 ATT2 =V5 =.781*F1 +.624 E5.611 ATT3 =V6 =.904*F1 +.427 E6.817 INT =F2 =.678*F1 +.735 D2.460 GOODNESS OF FIT SUMMARY FOR METHOD = ML CHI-SQUARE = 5.426 BASED ON 7 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS.60809

25. 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 3.730 3.2083.436 1.6871.6752.171 0.6210.6160.6051.373 1.0630.8640.4280.6711.397 0.8950.8180.5950.9120.663 1.498 /PRINT /LMTEST ! PROCESS =SIMULTANEOUS; ! SET=PVV,PFV,PFF,PDD,PEE; /WTEST /END GOODNESS OF FIT SUMMARY FOR METHOD = ML CHI-SQUARE = 10.808 BASED ON 7 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS.14722

26. 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 3.730 3.2083.436 1.6871.6752.171 0.6210.6160.6051.373 1.0630.8640.4280.6711.397 0.8950.8180.5950.9120.663 1.498 /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 4.389 3.792 4.410 1.935 1.855 2.385 1.454 1.453 0.989 1.914 1.087 1.309 0.841 0.961 1.480 1.623 1.701 1.175 1.279 1.220 1.971 !/PRINT !/LMTEST !/WTEST /END GOODNESS OF FIT SUMMARY FOR METHOD = ML INDEPENDENCE MODEL CHI-SQUARE = 526.203 ON 30 DEGREES OF FREEDOM CHI-SQUARE = 15.846 BASED ON 13 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS.25757

27. 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 4.389 3.792 4.410 1.935 1.855 2.385 1.454 1.453 0.989 1.914 1.087 1.309 0.841 0.961 1.480 1.623 1.701 1.175 1.279 1.220 1.971 !/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 3.730 3.2083.436 1.6871.6752.171 0.6210.6160.6051.373 1.0630.8640.4280.6711.397 0.8950.8180.5950.9120.663 1.498 /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 = 17.862 BASED ON 16 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS.33206