Intraction subsume main effect4/10/2023 ![]() ![]() The results are below.Īs you can see, the interaction effect test is statistically significant. In the interaction model, I’ll include temperature*pressure as an interaction effect. To learn how to recreate the continuous interaction plot using Excel, download this Excel file: Continuous Interaction Excel. Here’s the CSV data file if you want to try it yourself: Interactions_Continuous. The independent variables (processing time, temperature, and pressure) affect the dependent variable (product strength). Example of an Interaction Effect with Continuous Independent Variablesįor our next example, we’ll assess continuous independent variables in a regression model for a manufacturing process. However, that is not always the case, as you’ll see in the next example. Given the intentionally intuitive nature of our silly example, the consequence of disregarding the interaction effect is evident at a passing glance. That’s not a good choice despite what the main effects show! When you have statistically significant interactions, you cannot interpret the main effect without considering the interaction effects. We’ll make our decision based on the main effects plots below.īased on these plots, we’d choose hot dogs with chocolate sauce because they each produce higher enjoyment. However, imagine that we forgot to include the interaction effect and assessed only the main effects. Suppose we want to maximize satisfaction by choosing the best food and the best condiment. In the previous example, you can’t answer the question about which condiment is better without knowing the type of food. When you have statistically significant interaction effects, you can’t interpret the main effects without considering the interactions. Overlooking Interaction Effects is Dangerous! Which condiment is best? It depends on the type of food, and we’ve used statistics to demonstrate this effect. If you put mustard on ice cream or chocolate sauce on hot dogs, you won’t be happy! Conversely, satisfaction levels are higher for mustard when the food is a hot dog. The graph shows that enjoyment levels are higher for chocolate sauce when the food is ice cream. The crossed lines on the graph suggest that there is an interaction effect, which the significant p-value for the Food*Condiment term confirms. ![]()
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