March 2019
Beginner to intermediate
448 pages
13h 14m
English
Content preview from R Statistics Cookbook
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Type III
The final possibility is to calculate the sum of squares conditional on the interaction. This is uncommon, as we typically aren't interested in the main effects given that a significant interaction exists. If the interaction is not significative, then Type II has more power:
If the underlying design is balanced (the same amount of observations for each factor combination), the three of them will be equivalent. If they are not, they will differ. In general, Type II is preferred since we want to test an effect after controlling the other one, but we can't test the interaction using it. So, we generally prefer Type I initially to test ...
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