![]() Be wary that having this many parameters will penalize your Adj R^2. You will want 5 (races) x 2 (genders) = 10 - 2 terms, with one (say black and woman) of each category as the control variable. Because all possible values of these variables are, they basically just act as conditional intercept terms. ![]() I am assuming your dependent variable is health care costs or something of that form? The "interaction terms" in this sense are just a set of terms, for which only one will be a nonzero value for any given observation. Use multiple linear regression to test these hypotheses. This type of model would be used to find the probability of an event given a value of your dependent variable(s). ![]() You won't want to use a binary logistic regression.
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