car_ps: Generate Pocock-Simon minimization treatment assignments

In RobinCar: Robust Estimation and Inference in Covariate-Adaptive Randomization

Generate Pocock-Simon minimization treatment assignments

Description

Generate Pocock-Simon minimization treatment assignments

Usage

car_ps(z, treat, ratio, imb_measure, p_bc = 0.8)

Arguments

z	The car_strata design matrix
treat	A vector of length k (the number of treatment arms), which labels the treatment arms being compared.
ratio	A vector of length k (the number of treatment arms), which indicates the allocation ratio, e.g., c(1,1,1) for equal allocation with three treatment arms.
imb_measure	What measure of imbalance should be minimzed during randomization – either "Range" or "SD"
p_bc	The biased probability, i.e., the probability of assigning each patient to the arm that minimizes the imbalance. Default is 0.8

Value

res

treatment assignment vector

A vector of treatment assignments with labels from the ‘treat' argument, based on Pocock-Simon’s minimization.

Author(s)

Ting Ye Yanyao Yi

Examples

# Create car_strata variables
library(fastDummies)
library(dplyr)

x <- runif(100)
z <- cut(x, breaks=c(0, 0.25, 0.5, 0.75, 1.0))
z <- dummy_cols(z)
A <- car_ps(
  z=z[, 2:5],
  treat=c(0, 1, 2),
  ratio=c(1, 1, 1),
  imb_measure="Range"
)

RobinCar documentation built on May 29, 2024, 3:03 a.m.