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Interaction Effect


An interaction effect occurs when the effect of one explanatory variable on a response variable depends on the value of another explanatory variable. For two factors with levels 0 and 1 and cell means mu_(ij), the two-factor interaction contrast is

 mu_(11)-mu_(10)-mu_(01)+mu_(00).

It is zero when the two factor effects are additive. In a regression model, an interaction is commonly represented by a product term, for example

 E(Y|x_1,x_2)=beta_0+beta_1x_1+beta_2x_2+beta_(12)x_1x_2,

where beta_(12) measures the interaction on the scale of the model.


See also

ANOVA, Conditional Expectation, Factorial Experiment, General Linear Model, Regression

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References

Montgomery, D. C. Design and Analysis of Experiments, 8th ed. Hoboken, NJ: Wiley, 2013.

Cite this as:

Weisstein, Eric W. "Interaction Effect." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/InteractionEffect.html

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