sreg.rgen: Generate a Pseudo-Random Sample under the Stratified Block...

In sreg: Stratified Randomized Experiments

Generate a Pseudo-Random Sample under the Stratified Block Randomization Design

Description

The function generates the observed outcomes, treatment assignments, strata indicators, cluster indicators, cluster sizes, and covariates for estimating the treatment effect within the context of a stratified block randomization design under the covariate-adaptive randomization (CAR).

Usage

sreg.rgen(
  n,
  Nmax = 50,
  n.strata = 10,
  tau.vec = c(0),
  gamma.vec = c(0.4, 0.2, 1),
  cluster = TRUE,
  is.cov = TRUE,
  small.strata = FALSE,
  k = 3,
  treat.sizes = c(1, 1, 1)
)

Arguments

n	a total number of observations in a sample
Nmax	a maximum size of generated clusters (maximum number of observations in a cluster)
n.strata	an integer specifying the number of strata
tau.vec	a numeric 1 \times |\mathcal A| vector of treatment effects, where |\mathcal A| represents the number of treatments
gamma.vec	a numeric 1 \times 3 vector of parameters corresponding to covariates
cluster	a TRUE/FALSE argument indicating whether the dgp should use a cluster-level treatment assignment or individual-level
is.cov	a TRUE/FALSE argument indicating whether the dgp should include covariates or not
small.strata	a TRUE/FALSE argument indicating whether the data-generating process should use a small-strata design (e.g., matched pairs, n-tuples)
k	an integer specifying the number of units per stratum when small.strata = TRUE
treat.sizes	a numeric 1 \times (|\mathcal A| + 1) vector specifying the number of units assigned to each treatment within a stratum; the first element corresponds to control units (D = 0), the second to the first treatment (D = 1), and so on

Value

An object that is a 'data.frame' with n observations containing the generated values of the following variables:

• Y: a numeric n \times 1 vector of observed outcomes

• S: a numeric n \times 1 vector of strata indicators

• D: a numeric n \times 1 vector of treatments indexed by \{0, 1, 2, \ldots\}, where \code{D} = 0 denotes the control

• G.id: a numeric n \times 1 vector of cluster indicators

• X: a data.frame with columns representing the covariate values for every observation

Examples

data <- sreg.rgen(n = 1000, tau.vec = c(0), n.strata = 4, cluster = TRUE)

sreg documentation built on Aug. 25, 2025, 5:14 p.m.