I am doing a replication, and quite frankly, I don't know why the dummy variable is being used. I used the product type as an example, but I realize that was a bad choice. It is actually a numeric variable with product types being depicted as numbers (e.g., product type 33 which actually means "food," but the 33 is in numeric form in the data set; I apologize for the vagueness in this example, I thought it'd be clearer using the character values instead of saying I need 33=1, 39=2, and so forth since the values are not continuous 33, 34, 35, etc.). In the study I'm trying to replicate, they used dummy variables for the product type (though I'm unsure why, but I assume there's a reason that would affect my results?). The product type is meant to be a control variable, but from what I understand it functions just like any other independent variable. I can run a regular OLS regression with the variable as-is, without the dummy variables, but I'm not getting the correct results - they are actually way off, not just a little bit. So I was trying to figure out another way. From my regression I ultimately need the interaction term coefficients for the two groups (part of the interaction term in the equation below), and then their mean differences for each year. model: DV = Year Year*Group ProductType The previous codes I used to try and do the dummy variables include proc glmmod, and I also tried a macro code, but I no longer have the code because it was a mess and not what I needed.
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