I am new to Experimental Design. I would greatly appreciate if you could help.
Suppose one is interested in estimating a regression model with three explanatory variables (two of which are categorical) within the framework of experimental design. I need to come up with a way to study the purely experimental variance. How should go about it?
My initial idea was to replicate the experiment at any one combination of the centre of the continuous explanatory variable with levels of the two categorical variables and calculate the empirical corrected variance of the replicated responses but I am unsure whether this is the way to go. Shouldn't I rather take into account the various combined categories in some clever (and not too costly) way?
EDIT: For some perspective, suppose the categorical variables are called "education" (four levels, say) and "language" (two levels) for example, and that the continuous explanatory variable is called "salary".
My problem with my initial approach is that various selected combinations of levels may lead to drastically different values for the purely experimental variance.
Now, if we make $n_1, ..., n_8$ repetitions (respectively) at each combination of levels, how is one to estimate the purely experimental variance?