trimByPs: Trim persons by propensity score

In CohortMethod: Comparative Cohort Method with Large Scale Propensity and Outcome Models

Trim persons by propensity score

Description

Use the provided propensity scores to trim subjects with extreme scores or weights.

Usage

trimByPs(population, trimByPsArgs = createTrimByPsArgs(trimFraction = 0.05))

Arguments

population	A data frame with the three columns described below
trimByPsArgs	An object of type trimByPsArgs as created by the createTrimByPsArgs() function.

Details

The data frame should have the following three columns:

• rowId (numeric): A unique identifier for each row (e.g. the person ID).

• treatment (integer): Column indicating whether the person is in the target (1) or comparator (0) group.

• propensityScore (numeric): Propensity score.

Value

Returns a tibble with the same three columns as the input.

Examples

rowId <- 1:2000
treatment <- rep(0:1, each = 1000)
propensityScore <- c(runif(1000, min = 0, max = 1), runif(1000, min = 0, max = 1))
iptw <- ifelse(treatment == 1,
               mean(treatment == 1) / propensityScore,
               mean(treatment == 0) / (1 - propensityScore))
data <- data.frame(rowId = rowId,
                   treatment = treatment,
                   propensityScore = propensityScore,
                   iptw = iptw)
result1 <- trimByPs(data, createTrimByPsArgs(trimFraction = 0.05))
result2 <- trimByPs(data, createTrimByPsArgs(equipoiseBounds = c(0.3, 0.7)))
result3 <- trimByPs(data, createTrimByPsArgs(maxWeight = 10))

CohortMethod documentation built on March 21, 2026, 5:06 p.m.