Use the preference score to trim subjects that are not in clinical equipoise
trimByPsToEquipoise(population, bounds = c(0.3, 0.7))
A data frame with at least the three columns described below.
The upper and lower bound on the preference score for keeping persons.
Returns a tibble with the same three columns as the input.
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.
Walker AM, Patrick AR, Lauer MS, Hornbrook MC, Marin MG, Platt R, Roger VL, Stang P, and Schneeweiss S. (2013) A tool for assessing the feasibility of comparative effectiveness research, Comparative Effective Research, 3, 11-20
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 <- trimByPsToEquipoise(data) #> Population size after trimming is 833