APCEsummaryipw | R Documentation |
Summary of average principal causal effects (APCE) with ordinal decision with frequentist results.
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")
)
G1_est |
List generated from |
G2_est |
List generated from |
G3_est |
List generated from |
G4_est |
List generated from |
G5_est |
List generated from |
G1_boot |
List generated from |
G2_boot |
List generated from |
G3_boot |
List generated from |
G4_boot |
List generated from |
G5_boot |
List generated from |
name.group |
A list of character vectors for the label of five subgroups. |
A data.frame
that consists of mean and quantiles (2.5
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
)
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