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Multiple Linear Regression with Mediator

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Presentation on theme: "Multiple Linear Regression with Mediator"— Presentation transcript:

1 Multiple Linear Regression with Mediator

2 Conceptual Model Purchase Intention Satisfaction IV1 H1 H2 IV2 H11 H3
Indirect Effect H1 H2 H3 H4 H5 H11

3 Conceptual Model (direct and indirect effects)
Satisfaction IV1 IV2 IV3 IV4 IV5 Purchase Intention Indirect Effect Direct Effect H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11

4 Testing Mediator Effects
Three regression equations should be estimated Regressing the mediator on the IV--the IV must affect the mediator (Path A) Regressing the DV on the IV--the IV must affect the DV (Path C) Regressing the DV on both IV and on mediator- -mediator must affect the DV, and the effect of the IV on DV must be less than the effect in the second equation

5 Test Mediator Effect (Satisfaction)
Model 1: Mediator and IVs Model 2: DV and IVs Model 3: Full Model (with interactions) Regressing Satisfaction on IVs: Sat = b0 + b1(IV1) + b2(IV2) + b3(IV3) + b4(IV4) + b5(IV5) Regressing PI on IVs: PI = b0 + b1(IV1) + b2(IV2) + b3(IV3) + b4(IV4) + b5(IV5) Regressing PI on Satisfaction, Loyalty, and IVs: PI = b0 + b1(IV1) + b2(IV2) + b3(IV3) + b4(IV4) + b5(IV5) + + b6(IV1*Sat) + b7(IV2*Sat) + b8(IV3*Sat) + b9(IV4*Sat) + b10(IV5*Sat) + b11(Sat)

6 Conceptual Model Purchase Intention Satisfaction H1 IV1 H6 H17 H2 H7
For each IV, there are both direct effect and indirect effect from the IV to DV Considering the effects of IV1 on DV, the direct effect is tested by H1; whereas, the indirect effects are tested by H6 and H11 IV4 H5 H10 IV5

7 Conceptual Model Loyalty Purchase Intention Satisfaction
Test alternative hypothesis that H1: b1 ≠ 0 Loyalty IV1 H6 H17 H11-15 H2 H7 IV2 H16 Satisfaction Purchase Intention H3 H8 IV3 H9 H4 IV4 Regressing PI on Satisfaction, Loyalty, and IVs: PI = b0 + b1(IV1) + b2(IV2) + b3(IV3) + b4(IV4) + b5(IV5) + + b6(IV1*Sat) + b7(IV2*Sat) + b8(IV3*Sat) + b9(IV4*Sat) + b10(IV5*Sat) + b11(Sat) H5 H10 IV5

8 Conceptual Model Loyalty Purchase Intention Satisfaction
Test alternative hypothesis that H6: b6 ≠ 0 Loyalty IV1 H6 H17 H11-15 H2 H7 IV2 H16 Satisfaction Purchase Intention H3 H8 IV3 H9 H4 IV4 Regressing PI on Satisfaction, Loyalty, and IVs: PI = b0 + b1(IV1) + b2(IV2) + b3(IV3) + b4(IV4) + b5(IV5) + + b6(IV1*Sat) + b7(IV2*Sat) + b8(IV3*Sat) + b9(IV4*Sat) + b10(IV5*Sat) + b11(Sat) H5 H10 IV5

9 Conceptual Model Purchase Intention Satisfaction
Test alternative hypothesis that H11: b11 ≠ 0 H1 IV1 H6 H17 H2 H7 IV2 H16 Satisfaction Purchase Intention H11 H3 H8 IV3 H9 H4 IV4 Regressing PI on Satisfaction, Loyalty, and IVs: PI = b0 + b1(IV1) + b2(IV2) + b3(IV3) + b4(IV4) + b5(IV5) + + b6(IV1*Sat) + b7(IV2*Sat) + b8(IV3*Sat) + b9(IV4*Sat) + b10(IV5*Sat) + b11(Sat) H5 H10 IV5

10 Test Mediator Effect (Satisfaction)
Model 1: Mediator and IVs check whether an IV effects mediator at least one of the coefficients/parameter estimates is not equal to 0 (at least b1, b2, b3, b4, or b5 ≠ 0) Regressing Satisfaction on IVs: Sat = b0 + b1(IV1) + b2(IV2) + b3(IV3) + b4(IV4) + b5(IV5)

11 Test Mediator Effect (Satisfaction)
Model 2: DV and IVs check whether an IV effects DV at least one of the coefficients/parameter estimates is not equal to 0 (at least b1,2, b2,2, b3,2, b4,2, or b5,2 ≠ 0) Regressing PI on IVs: PI = b0 + b1,2(IV1) + b2,2(IV2) + b3,2(IV3) + b4,2(IV4) + b5,2(IV5)

12 Test Mediator Effect (Satisfaction)
Model 3: Full Model (with interactions) check whether Mediator effects DV; therefore, b16 must not equal to 0 (b16 ≠ 0) check whether the effect of the IV on DV must be less than the same effect in the second equation; therefore, one of these must be true: Regressing PI on Satisfaction, Loyalty, and IVs: PI = b0 + b1,3(IV1) + b2,3(IV2) + b3,3(IV3) + b4,3(IV4) + b5,3(IV5) + + b6(IV1*Sat) + b7(IV2*Sat) + b8(IV3*Sat) + b9(IV4*Sat) + b10(IV5*Sat) + b11(Sat) b1,3 < b1,2 b2,3 < b2,2 b3,3 < b3,2 b4,3 < b4,2 b5,3 < b5,2


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