1 / 16

G89.2229 Multiple Regression Week 4 Monday

G89.2229 Lect 4M. Suppression. Sometimes the semipartial effect for X1 (i.e. b1) in Y = b0 b1X1 b2X2 e is larger in absolute magnitude than the bivariate effect in Y = b0 b1X1 eThis has been called suppressionExample:X1 is stressY is distressX2 is copingClassic pattern is when one of

ford
Download Presentation

G89.2229 Multiple Regression Week 4 Monday

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. G89.2229 Lect 4M Interpreting multiple regression weights: suppression and spuriousness. Partial and semi-partial correlations Multiple regression in matrix terms G89.2229 Multiple Regression Week 4 (Monday)

    2. G89.2229 Lect 4M Suppression Sometimes the semipartial effect for X1 (i.e. b1) in Y = b0 + b1X1 + b2X2 + e is larger in absolute magnitude than the bivariate effect in Y = b0 + b1X1 + e This has been called suppression Example: X1 is stress Y is distress X2 is coping Classic pattern is when one of the three correlations is negative.

    3. G89.2229 Lect 4M Spurious effect Consider a path model that resembles the mediation model. Suppose that there is a bivariate association between X and Y, but when W is considered, the semipartial effect b is zero. The original association is often said to be "spurious". It is explained by the common cause, W.

More Related