main effect

If you have significant a significant interaction effect and non-significant main effects, would you interpret the interaction effect?

It’s a question I get pretty often, and it’s a more straightforward answer than most.

(more…)

29 comments

One of those “rules” about statistics you often hear is that you can’t interpret a main effect in the presence of an interaction.

Stats professors seem particularly good at drilling this into students’ brains.

Unfortunately, it’s not true.

At least not always. (more…)

12 comments

A Linear Regression Model with an interaction between two predictors (X₁ and X₂) has the form: 

Y = B₀ + B₁X₁ + B₂X₂ + B₃X₁*X₂.

It doesn’t really matter if X₁ and X₂ are categorical or continuous, but let’s assume they are continuous for simplicity.

One important concept is that B₁ and B₂ are not main effects, the way they would be if (more…)

15 comments