PlotAPCE {aihuman}

Plot APCE

Description

See Figure 4 for example.

Usage

PlotAPCE(
  res,
  y.max = 0.1,
  decision.labels = c("signature bond", "small cash bond", "large cash bond"),
  shape.values = c(16, 17, 15),
  col.values = c("blue", "black", "red", "brown"),
  label = TRUE,
  r.labels = c("safe", "easily\npreventable", "prevent-\nable", "risky\n"),
  label.position = c("top", "top", "top", "top"),
  top.margin = 0.01,
  bottom.margin = 0.01,
  name.group = c("Overall", "Female", "Male", "Non-white\nMale", "White\nMale"),
  label.size = 4
)

Arguments

res

A data.frame generated with APCEsummary().

y.max

Maximum value of y-axis.

decision.labels

Labels of decisions (D).

shape.values

Shape of point for each decisions.

col.values

Color of point for each principal stratum.

label

A logical argument whether to specify label of each principal stratum. The default is TRUE.

r.labels

Label of each principal stratum.

label.position

The position of labels.

top.margin

Top margin of labels.

bottom.margin

Bottom margin of labels.

name.group

A character vector including the labels of five subgroups.

label.size

Size of label.

Value

A ggplot.

Examples

data(synth)
sample_mcmc = AiEvalmcmc(data = synth, n.mcmc = 10)
subgroup_synth = list(1:nrow(synth),which(synth$Sex==0),which(synth$Sex==1),
                      which(synth$Sex==1&synth$White==0),which(synth$Sex==1&synth$White==1))
sample_apce = CalAPCE(data = synth, mcmc.re = sample_mcmc, 
                      subgroup = subgroup_synth)
sample_apce_summary = APCEsummary(sample_apce[["APCE.mcmc"]])
PlotAPCE(sample_apce_summary, y.max = 0.25, decision.labels = c("signature","small cash",
         "middle cash","large cash"), shape.values = c(16, 17, 15, 18), 
         col.values = c("blue", "black", "red", "brown", "purple"), label = FALSE)