PrinSDiag: Evaluate covariate balance for the principal score model

In PDRobust: Robust Longitudinal Effects Under Truncation by Death

Evaluate covariate balance for the principal score model

Description

Calculates a standardized balance statistic for each numeric covariate at the cutoff time after accounting for treatment assignment and estimated survival. Values nearer zero indicate better balance between the weighted treatment groups.

Usage

PrinSDiag(data, ps_fo, prin_fo)

Arguments

data	Data prepared by DataStandard().
ps_fo	propensity score model formula
prin_fo	principal score model formula

Details

The function fits both the propensity score and principal score models. It uses all observed times from baseline through cutoff to estimate cumulative survival probabilities, limits propensity scores to ⁠[0.01, 0.99]⁠, and then calculates the balance statistics at the cutoff time.

Value

A PrinSDiag object containing the standardized balance statistics, estimated probabilities, and a diagnostic plot. Balance statistics 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 <- PrinSDiag(
  pd_dat,
  A ~ X1 + X2 + X4,
  S ~ X1 + X2 + X4 + A + time
)
result$statistics

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