Summary statistics of covariates within the always-survivor principal stratum

Estimates the user-specified quantile for continuous covariates and the mean of covariates for subjects within the always-survivor principal stratum.

Usage

QR(data, prin_fo, quantile_level = 0.5)

Arguments

data: Data prepared by DataStandard().
prin_fo: principal score model formula
quantile_level: One or more quantiles to estimate, expressed as probabilities strictly between 0 and 1. Defaults to the median (0.5).

Value

A QR object containing the weighted means, requested quantiles, variable-type indicators, and weights. Reported means and quantiles are rounded to three decimal places.

Details

QR() uses estimated survival probabilities under treatment 0 to weight the numeric variables listed in interest_vars. It reports a weighted mean for every variable. For variables with more than two observed values, it also reports the requested weighted quantiles. Variables with no more than two observed values are treated as binary and receive a mean but no quantile.

Examples

# \donttest{
data("BiSample", package = "PDRobust")
map <- Mapping(
  id = "id", time = "time", treatment = "A",
  survival = "S", outcome = "Y",
  baseline_time = 0, cutoff_time = 2,
  covariates = c("X1", "X2", "X4"),
  interest_vars = c("X1", "X2"), y_type = "B"
)
pd_dat <- DataStandard(BiSample, map)
result <- QR(
  pd_dat,
  S ~ X1 + X2 + X4 + A + time,
  quantile_level = c(0.25, 0.5, 0.75)
)
result$mean
#>    X1    X2 
#> 0.140 0.141 
# }