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When to include the interaction but not the main effects in a model?
In my experience, not only is it necessary to have all lower order effects in the model when they are connected to higher order effects, but it is also important to properly model (e.g., allowing to be nonlinear) main effects that are seemingly unrelated to the factors in the interactions of interest.
How are independent variables affected by interaction effects?
In more complex study areas, the independent variables might interact with each other. Interaction effects indicate that a third variable influences the relationship between an independent and dependent variable. This type of effect makes the model more complex, but if the real world behaves this way, it is critical to incorporate it in your model.
What’s the difference between main effect and interaction effect?
The main effect portion is the effect that is independent of all other variables in the model–only the value of the IV itself matters. The interaction effect is the portion that does depend on the values of the other variable(s) in the interaction term. Together, the main effect and interaction effect sum to the total effect.
Is it really necessary to include both main effects?
Is it really necessary to include both main effects when the interaction is present? The simple answer is no, you don’t always need main effects when there is an interaction. However, the interaction term will not have the same meaning as it would if both main effects were included in the model.
When to add interaction terms in an ANOVA?
In an ANOVA, adding interaction terms still leaves the main effects as main effects. That is, as long as the data are balanced, the main effects and the interactions are independent. The main effect is still telling you if there is an overall effect of that variable after accounting for other variables in the model.
Why do you keep main effects in a model?
The reason to keep the main effects in the model is for identifiability. Hence, if the purpose is statistical inference about each of the effects, you should keep the main effects in the model.