trimByPs: Trim persons by propensity score

In escott12/CohortMethod: New-User Cohort Method with Large Scale Propensity and Outcome Models

Description

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

Usage

trimByPs(population, trimFraction = 0.05)

Arguments

population	A data frame with the three columns described below
trimFraction	This fraction will be removed from each treatment group. In the target group, persons with the highest propensity scores will be removed, in the comparator group person with the lowest scores will be removed.

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))
data <- data.frame(rowId = rowId, treatment = treatment, propensityScore = propensityScore)
result <- trimByPs(data, 0.05)

escott12/CohortMethod documentation built on Dec. 20, 2021, 6:37 a.m.