aihuman (version 1.0.0)

APCEsummaryipw: Summary of APCE for frequentist analysis

Description

Summary of average principal causal effects (APCE) with ordinal decision with frequentist results.

Usage

APCEsummaryipw(
  G1_est,
  G2_est,
  G3_est,
  G4_est,
  G5_est,
  G1_boot,
  G2_boot,
  G3_boot,
  G4_boot,
  G5_boot,
  name.group = c("Overall", "Female", "Male", "Non-white\nMale", "White\nMale")
)

Value

A data.frame that consists of mean and quantiles (2.5

Arguments

G1_est

List generated from CalAPCEipw for the first subgroup.

G2_est

List generated from CalAPCEipw for the second subgroup.

G3_est

List generated from CalAPCEipw for the third subgroup.

G4_est

List generated from CalAPCEipw for the fourth subgroup.

G5_est

List generated from CalAPCEipw for the fifth subgroup.

G1_boot

List generated from BootstrapAPCEipw for the first subgroup.

G2_boot

List generated from BootstrapAPCEipw for the second subgroup.

G3_boot

List generated from BootstrapAPCEipw for the third subgroup.

G4_boot

List generated from BootstrapAPCEipw for the fourth subgroup.

G5_boot

List generated from BootstrapAPCEipw for the fifth subgroup.

name.group

A list of character vectors for the label of five subgroups.

Examples

data(synth)
synth$SexWhite <- synth$Sex * synth$White
freq_apce <- CalAPCEipw(synth)
boot_apce <- BootstrapAPCEipw(synth, rep = 10)
# subgroup analysis
data_s0 <- subset(synth, synth$Sex == 0, select = -c(Sex, SexWhite))
freq_s0 <- CalAPCEipw(data_s0)
boot_s0 <- BootstrapAPCEipw(data_s0, rep = 10)
data_s1 <- subset(synth, synth$Sex == 1, select = -c(Sex, SexWhite))
freq_s1 <- CalAPCEipw(data_s1)
boot_s1 <- BootstrapAPCEipw(data_s1, rep = 10)
data_s1w0 <- subset(synth, synth$Sex == 1 & synth$White == 0, select = -c(Sex, White, SexWhite))
freq_s1w0 <- CalAPCEipw(data_s1w0)
boot_s1w0 <- BootstrapAPCEipw(data_s1w0, rep = 10)
data_s1w1 <- subset(synth, synth$Sex == 1 & synth$White == 1, select = -c(Sex, White, SexWhite))
freq_s1w1 <- CalAPCEipw(data_s1w1)
boot_s1w1 <- BootstrapAPCEipw(data_s1w1, rep = 10)

freq_apce_summary <- APCEsummaryipw(
  freq_apce, freq_s0, freq_s1, freq_s1w0, freq_s1w1,
  boot_apce, boot_s0, boot_s1, boot_s1w0, boot_s1w0
)
PlotAPCE(freq_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
)