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

Msam07, Albert Satorra

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Examples with Coupon data (Bagozzi, 1994)


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Data from Bagozzi, Baumgartner, and Yi (1992), on “coupon usage” .

Sample A: Action oriented women (n = 85)Intentions #1 4.389Intentions #2 3.792 4.410Behavior 1.935 1.855 2.385Attitudes #1 1.454 1.453 0.989 1.914Attitudes #2 1.087 1.309 0.841 0.961 1.480Attitudes #3 1.623 1.701 1.175 1.279 1.220 1.971

Sample B: State oriented women (n = 64)Intentions #1 3.730Intentions #2 3.208 3.436Behavior 1.687 1.675 2.171Attitudes #1 0.621 0.616 0.605 1.373Attitudes #2 1.063 0.864 0.428 0.671 1.397Attitudes #3 0.895 0.818 0.595 0.912 0.663 1.498


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Variables

/LABELS V1 = Intentions1; V2 = Intentions2; V3 = Behavior; V4 = Attitudes1; V5 = Attitudes2; V6 = Attitudes3;


4

V4 V1

E1

Simple linear regression


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/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


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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


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V4 V1

V3

E1

Bivariate regression

E3


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/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



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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


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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



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V4 V1

V3

E1

E3

Bivariate regression(correlated disturbance)


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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


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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



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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


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V4 V1

V3

E1

E3

Simultaneous equations


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/TITLEPath 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; /EQUATIONSV1 = *V4 + E1;V3 = *V1 + *V4 + E3;/VARIANCESV4 = *;E1 = *;E3 = *;/COVARIANCES/MATRIX4.389 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



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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


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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


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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



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F1 V1

V3

E1

E3

V4

V5

V6

E4

E5

E6

SEM multiple indicators


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SEM: Action oriented

/TITLESEM 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; /EQUATIONSV4 = *F1 + E4;V5 = *F1 + E5;V6 = *F1 + E6;V1 = *F1 + E1;V3 = *F1 + *V1 + E3;/VARIANCESF1 = 1;E1 = *;E3 TO E6 = *;/COVARIANCES/MATRIX4.389 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


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F1 F2

V3

D2

E3

SEM multiple indicators

V4

V5

V6

V1

V2

E4

E5

E6

E1

E2


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/TITLEPath 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;/EQUATIONSV4 = *F1 + E4;V5 = *F1 + E5;V6 = *F1 + E6;V1 = 1F2 + E1;V2 = *F2 + E2;F2 = *F1 + D2;V3 = *F1 + *F2 + E3;/VARIANCESF1 = 1; D2 =* ; E1 T0 E6 = *;/COVARIANCES/MATRIX4.389 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



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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@


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


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SEM: State oriented /TITLEPath 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;/EQUATIONSV4 = *F1 + E4;V5 = *F1 + E5;V6 = *F1 + E6;V1 = 1F2 + E1;V2 = *F2 + E2;F2 = *F1 + D2;V3 = *F1 + *F2 + E3;/VARIANCESF1 = 1; D2 =* ; E1 =*;E2 =*;E3 T0 E6 = *;

/COVARIANCES!E3,E2=*;/MATRIX3.7303.208 3.4361.687 1.675 2.1710.621 0.616 0.605 1.3731.063 0.864 0.428 0.671 1.3970.895 0.818 0.595 0.912 0.6631.498 /PRINT/LMTEST! PROCESS =SIMULTANEOUS;! SET=PVV,PFV,PFF,PDD,PEE;/WTEST/END


CHI-SQUARE = 10.808 BASED ON 7 DEGREES OF FREEDOM PROBABILITY VALUE FOR THE CHI-SQUARE STATISTIC IS .14722


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SEM: multiple group/TITLEstate 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;/EQUATIONSV4 = *F1 + E4;V5 = *F1 + E5;V6 = *F1 + E6;V1 = 1F2 + E1;V2 = *F2 + E2;F2 = *F1 + D2;V3 = *F1 + *F2 + E3;/VARIANCESF1 = 1; D2 =* ; E1 T0 E6 = *;/COVARIANCESE3,E2=*;/MATRIX3.730

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 0.6631.498 /PRINT/LMTESTPROCESS =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


INDEPENDENCE MODEL CHI-SQUARE = 526.203 ON 30 DEGREES OF FREEDOM



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/TITLEAction 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;/EQUATIONSV4 = *F1 + E4;V5 = *F1 + E5;V6 = *F1 + E6;V1 = 1F2 + E1;V2 = *F2 + E2;F2 = *F1 + D2;V3 = *F1 + *F2 + E3;/VARIANCESF1 = 1; D2 =* ; E1 T0 E6 = *;/COVARIANCES/MATRIX4.389 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/TITLEstate 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;/EQUATIONSV4 = *F1 + E4;V5 = *F1 + E5;V6 = *F1 + E6;V1 = 1F2 + E1;V2 = *F2 + E2;F2 = *F1 + D2;V3 = *F1 + *F2 + E3;/VARIANCESF1 = 1; D2 =* ; E1 T0 E6 = *;/COVARIANCESE3,E2=*;/MATRIX3.7303.208 3.4361.687 1.675 2.1710.621 0.616 0.605 1.3731.063 0.864 0.428 0.671 1.3970.895 0.818 0.595 0.912 0.6631.498 /PRINT/LMTESTPROCESS =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



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

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