aihuman (version 1.0.0)

plot_agreement: Visualize Agreement

Description

Visualize the agreement between human decisions and AI recommendations using a difference-in-means estimator of an indicator \(1\{D_i = A_i\}\). Generate a plot based on the overall agreement and subgroup-specific agreement.

Usage

plot_agreement(
  Y,
  D,
  Z,
  A,
  subgroup1,
  subgroup2,
  label.subgroup1 = "Subgroup 1",
  label.subgroup2 = "Subgroup 2",
  x.order = NULL,
  p.title = NULL,
  p.lb = -0.3,
  p.ub = 0.3,
  y.lab = "Impact of PSA"
)

Value

A ggplot object.

Arguments

Y

An observed outcome (binary: numeric vector of 0 or 1).

D

An observed decision (binary: numeric vector of 0 or 1).

Z

A treatment indicator (binary: numeric vector of 0 or 1).

A

An AI recommendation (binary: numeric vector of 0 or 1).

subgroup1

A pretreatment covariate used for subgroup analysis (vector).

subgroup2

A pretreatment covariate used for subgroup analysis (vector).

label.subgroup1

A label for subgroup1 (character). Default "Subgroup 1".

label.subgroup2

A label for subgroup2 (character). Default "Subgroup 2".

x.order

An order for the x-axis (character vector). Default NULL.

p.title

A title for the plot (character). Default NULL.

p.lb

A lower bound for the y-axis (numeric). Default -0.3.

p.ub

An upper bound for the y-axis (numeric). Default 0.3.

y.lab

A label for the y-axis (character). Default "Impact of PSA".

Examples

plot_agreement(
  Y = NCAdata$Y,
  D = ifelse(NCAdata$D == 0, 0, 1),
  Z = NCAdata$Z,
  A = PSAdata$DMF,
  subgroup1 = ifelse(NCAdata$White == 1, "White", "Non-white"),
  subgroup2 = ifelse(NCAdata$Sex == 1, "Male", "Female"),
  label.subgroup1 = "Race",
  label.subgroup2 = "Gender",
  x.order = c("Overall", "Non-white", "White", "Female", "Male")
)