You build a model predicting blood pressure as a function of three variables: weight (numeric) age (numeric) income (categorical: low, medium, high) You first specify your model as: blood pressure ~ age * income + weight How many parameters (k) does your model have? (Remember, we do not count the grand mean in k)
You build a model predicting blood pressure as a function of three variables:
weight (numeric)
age (numeric)
income (categorical: low, medium, high)
You first specify your model as:
blood pressure ~ age * income + weight
How many parameters (k) does your model have? (Remember, we do not count the grand mean in k)
You change the above model specification to be:
blood pressure ~ age * income + weight * income
How many parameters does your model have now?
You change your model to include the three-way interaction (which, remember, includes all two-way interactions and main effects, too!)
Your model now looks like this:
blood pressure ~ age * income * weight
How many parameters does your model have now?
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