TABLE 1.

Distributions of Variables in Data Generation Models 1 and 2

Variable	Analogous Social Position	Model 1: Categorical Inputs		Model 2: Mixed Inputs (Categorical And Continuous)
		Type	Distribution	Type	Distribution
X1	Income	Categorical	P(X1=0) = 0.25 P(X1=1) = 0.25 P(X1=2) = 0.25 P(X1=3) = 0.25	Continuous (split in quartiles to create intersections for estimation)	Mean = 0, Variance = 1
X2	Racialization (person of color, non-POC)	Binary	P(X2=1) = 0.2	Binary	P(X2=1) = 0.2
X3	Sex/gender (male, female)	Binary	P(X3=1) = 0.5	Binary	P(X3=1) = 0.5
X4	Education (completed postsecondary, did not complete)	Binary	P(X4=1 X3=0) = 0.4 P(X4=1 X3=1) = 0.7	Binary	P(X4=1 X3=0) = 0.4 P(X4=1 X3=1) = 0.7
X5	Immigrant status (immigrant, nonimmigrant)	Binary	P(X5=1) = 0.25	Binary	P(X5=1) = 0.25
X6	Age	Categorical	P(X6=0) = 0.33 P(X6=1) = 0.33 P(X6=2) = 0.33	Continuous (split in tertiles to create intersections for estimation)	Mean = 0, Variance = 1