In regression with multiple explanatory categorical variables, how should I model the problem to compare the effects of the categorical variables with each other?
Most contrast coding schemes (e.g. also on Wikipedia) seem to be designed (or at least, that's how they are described) to compare the effects of different levels within a given categorical variable (e.g. German vs British nationality). But what if I want to compare contributions between categorical variables?
For example, say that we want to estimate the contribution of two explanatory categorical variables (dress size and color) to a single dependent variable (dress price). How can I design my coding to measure interpretable contributions of size and color to price?