View source: R/ability_human.R
plot_diff_human | R Documentation |
Visualize the the difference in risk between human+AI and human decision makers using difference-in-means estimators. Generate a plot based on the overall agreement and subgroup-specific agreement.
plot_diff_human(
Y,
D,
Z,
l01 = 1,
subgroup1,
subgroup2,
label.subgroup1 = "Subgroup 1",
label.subgroup2 = "Subgroup 2",
x.order = NULL,
p.title = NULL,
p.lb = -1,
p.ub = 1,
y.lab = "Impact of PSA",
p.label = c("PSA harms", "PSA helps")
)
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). |
l01 |
Ratio of the loss between false positives and false negatives. Default 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 -1. |
p.ub |
An upper bound for the y-axis (numeric). Default 1. |
y.lab |
A label for the y-axis (character). Default "Impact of PSA". |
p.label |
A vector of two labels for the annotations (character). Default c("PSA harms", "PSA helps"). |
A ggplot object.
plot_diff_human(
Y = NCAdata$Y,
D = ifelse(NCAdata$D == 0, 0, 1),
Z = NCAdata$Z,
l01 = 1,
subgroup1 = ifelse(NCAdata$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"),
p.title = NULL, p.lb = -0.3, p.ub = 0.3
)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.