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Examples with Coupon data (Bagozzi, 1994)

This study examines the relationship between attitudes, intentions, and behavior related to coupon usage among action-oriented and state-oriented women.

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Examples with Coupon data (Bagozzi, 1994)

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

  2. Msam07, Albert Satorra Data from Bagozzi, Baumgartner, and Yi (1992), on “coupon usage” . Sample A: Action oriented women (n = 85) Intentions #1 4.389 Intentions #2 3.792 4.410 Behavior 1.935 1.855 2.385 Attitudes #1 1.454 1.453 0.989 1.914 Attitudes #2 1.087 1.309 0.841 0.961 1.480 Attitudes #3 1.623 1.701 1.175 1.279 1.220 1.971 Sample B: State oriented women (n = 64) Intentions #1 3.730 Intentions #2 3.208 3.436 Behavior 1.687 1.675 2.171 Attitudes #1 0.621 0.616 0.605 1.373 Attitudes #2 1.063 0.864 0.428 0.671 1.397 Attitudes #3 0.895 0.818 0.595 0.912 0.663 1.498

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

  4. Msam07, Albert Satorra Simple linear regression E1 V4 V1

  5. Msam07, Albert Satorra Simple linear regression /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

  6. Msam07, Albert Satorra 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 Bivariate regression E1 V4 V1 V3 E3

  8. Bivariate regression Msam07, Albert Satorra /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

  9. Msam07, Albert Satorra 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 Bivariate regression 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

  11. Msam07, Albert Satorra Bivariate regression (correlated disturbance) E1 V4 V1 V3 E3

  12. Bivariate regression (correlated disturbances) Msam07, Albert Satorra /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. Bivariate regression (correlated disturbance) Msam07, Albert Satorra 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

  14. Bivariate regression (correlated disturbance) Msam07, Albert Satorra 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 Simultaneous equations E1 V4 V1 E3 V3

  16. Msam07, Albert Satorra Simultaneous equations /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

  17. Msam07, Albert Satorra 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 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 Simultaneous equations 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

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

  21. Msam07, Albert Satorra 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 SEM multiple indicators E4 D2 V4 E1 V1 E5 F1 F2 V5 E2 V2 E6 V6 E3 V3

  23. Msam07, Albert Satorra SEM: Action oriented /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

  24. Msam07, Albert Satorra SEM: Action oriented 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@ 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 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

  25. Msam07, Albert Satorra 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 3.208 3.436 1.687 1.675 2.171 0.621 0.616 0.605 1.373 1.063 0.864 0.428 0.671 1.397 0.895 0.818 0.595 0.912 0.663 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. SEM: multiple group Msam07, Albert Satorra /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 /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 3.208 3.436 1.687 1.675 2.171 0.621 0.616 0.605 1.373 1.063 0.864 0.428 0.671 1.397 0.895 0.818 0.595 0.912 0.663 1.498 /PRINT /LMTEST PROCESS =SIMULTANEOUS; SET=PVV,PFV,PFF,PDD,PEE; /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 SEM: multiple group /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 /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 3.208 3.436 1.687 1.675 2.171 0.621 0.616 0.605 1.373 1.063 0.864 0.428 0.671 1.397 0.895 0.818 0.595 0.912 0.663 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

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