Lecture 13 Moderation
PSY 251 Lecture 13 DataCamp Moderation ! !
Learning by doing 1
An example • X: Experimental manipulation – Stereotype threat
• Y: Behavioral outcome – IQ test score
• Z: Moderator – Working memory capacity (WMC)
Moderation • A moderator variable (Z) will enhance a regression model if the relationship between X and Y varies as a function of Z
Moderation • Experimental research – The manipulation of an IV (X) causes change in a DV (Y) – A moderator variable (Z) implies that the effect of the IV on the DV (X on Y) is NOT consistent across the distribution of Z
Moderation • Correlational research – Assume a correlaton between X and Y – A moderator variable (Z) implies that the correlation between X and Y is NOT consistent across the distribution of Z
Moderation model • If both X and Z are continuous – Y = B0 + B1X + B2Z + B3(X*Z) + e
Moderation model • If X is categorical* and Z is continuous – Y = B0 + B1(D1) + B2(D2) + B3Z + B4(D1*Z) + B5(D2*Z) e *3 levels of X
How to test for moderation • If both X and Z are continuous – Model 1: No moderation • Y = B0 + B1X + B2Z + e
– Model 2: Moderation
• Y = B0 + B1X + B2Z + B3(X*Z) + e
How to test for moderation • If X is categorical* and Z is continuous – Model 1: No moderation • Y = B0 + B1(D1) + B2(D2) + B3Z + e
– Model 2: Moderation
• Y = B0 + B1(D1) + B2(D2) + B3Z + B4(D1*Z) + B5(D2*Z) + e
How to test for moderation • Compare Model 1 and Model 2 in terms of 2 overall variance explained, that is, R – NHST available for this comparison
• Evaluate B values for predictors associated with the moderation effect – (X*Z) – (D1*Z) and (D2*Z)
Learning by doing 1
An example • X: Experimental manipulation – Stereotype threat
• Y: Behavioral outcome – IQ test score
• Z: Moderator – Working memory capacity (WMC)
Moderation • A moderator variable (Z) will enhance a regression model if the relationship between X and Y varies as a function of Z
Moderation • Experimental research – The manipulation of an IV (X) causes change in a DV (Y) – A moderator variable (Z) implies that the effect of the IV on the DV (X on Y) is NOT consistent across the distribution of Z
Moderation • Correlational research – Assume a correlaton between X and Y – A moderator variable (Z) implies that the correlation between X and Y is NOT consistent across the distribution of Z
Moderation model • If both X and Z are continuous – Y = B0 + B1X + B2Z + B3(X*Z) + e
Moderation model • If X is categorical* and Z is continuous – Y = B0 + B1(D1) + B2(D2) + B3Z + B4(D1*Z) + B5(D2*Z) e *3 levels of X
How to test for moderation • If both X and Z are continuous – Model 1: No moderation • Y = B0 + B1X + B2Z + e
– Model 2: Moderation
• Y = B0 + B1X + B2Z + B3(X*Z) + e
How to test for moderation • If X is categorical* and Z is continuous – Model 1: No moderation • Y = B0 + B1(D1) + B2(D2) + B3Z + e
– Model 2: Moderation
• Y = B0 + B1(D1) + B2(D2) + B3Z + B4(D1*Z) + B5(D2*Z) + e
How to test for moderation • Compare Model 1 and Model 2 in terms of 2 overall variance explained, that is, R – NHST available for this comparison
• Evaluate B values for predictors associated with the moderation effect – (X*Z) – (D1*Z) and (D2*Z)
