ParetoR: ParetoR

In Diversity-ParetoOptimal/ParetoR: Estimates Pareto-Optimal solution for diversity hiring

ParetoR

Description

Command function to run Pareto-Optimal algorithm.

Usage

ParetoR(prop, sr, d, R, Spac = 20, graph = TRUE, display_solution = TRUE)

Arguments

prop	Proportion of minority applicants in full applicant pool
sr	Selection ratio
d	Subgroup difference
R	Correlation matrix
Spac	Determines the number of Pareto-optimal solutions, defaulted to 20
graph	If TRUE, plots will be generated for Pareto-optimal curve and predictor weights
display_solution	If TRUE, Pareto-optimal solutions will be printed

Value

out Pareto-Optimal solution with criterion values (Pareto_Fmat) and predictor weights (Pareto_Xmat)

Examples

# Specify inputs
# (1) Proportion of minority applicants (prop) = (# of minority applicants)/(total # of applicants)
prop <- 1/4
# (2) Selection ratio (sr) = (# of selected applicants)/(total # of applicants)
sr <- 0.10
# (3) Subgroup differences (d): standardized mean differences between minority
# and majority subgroups (i.e., majority - minority), on each predictor (in applicant pool)
d <- c(1.00, 0.23, 0.09, 0.33)
# (4) Correlation matrix (R) = criterion & predictor inter-correlation matrix (in applicant pool)
# Format: Predictor_1, ..., Predictor_n, Criterion
R <- matrix(c(1, .24, .00, .19, .30,
              .24, 1, .12, .16, .30,
              .00, .12, 1, .51, .18,
              .19, .16, .51, 1, .28,
              .30, .30, .18, .28, 1),
            (length(d)+1),(length(d)+1))
# Fit Pareto-optimal model
out = ParetoR(prop, sr, d, R)

Diversity-ParetoOptimal/ParetoR documentation built on May 8, 2024, 12:08 a.m.