1 / 12

Multiple Linear Regression with Mediator

Multiple Linear Regression with Mediator. Conceptual Model. IV1. H 1. H 2. IV2. H 11. Satisfaction. Purchase Intention. H 3. IV3. H 4. IV4. H 5. IV5. Indirect Effect. Conceptual Model (direct and indirect effects). H 1. IV1. H 6. H 2. H 7. IV2. H 11. Satisfaction.

hewitt
Download Presentation

Multiple Linear Regression with Mediator

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Multiple Linear Regressionwith Mediator

  2. Conceptual Model IV1 H1 H2 IV2 H11 Satisfaction Purchase Intention H3 IV3 H4 IV4 H5 IV5 Indirect Effect

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

  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 H1 IV1 H6 H17 H2 H7 IV2 H16 Satisfaction Purchase Intention H11 H3 H8 IV3 H9 H4 • 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 H1 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 H1 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 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 H5 H10 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) 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) 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) • 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: • b1,3 < b1,2 • b2,3 < b2,2 • b3,3 < b3,2 • b4,3 < b4,2 • b5,3 < b5,2

More Related