QR: Summary statistics of covariates within the always-survivor...

In PDRobust: Robust Longitudinal Effects Under Truncation by Death

Summary statistics of covariates within the always-survivor principal stratum

Description

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).

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.

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.

Examples

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

PDRobust documentation built on Oct. 2, 2026, 5:09 p.m.