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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

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G89.2229 Multiple Regression Week 4 Monday

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    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.

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