IBDInfer {IBDInfer} | R Documentation |
Design-based Inference for Incomplete Block Designs
Description
Conduct the design-based inference for incomplete block designs.
Usage
IBDInfer(y, b, z, g, w = c("Unit", "Block"), alpha = 0.05, data = NULL)
Arguments
y |
Observed outcomes. |
b |
Block identifier (ID). |
z |
Assigned treatments. |
g |
A contrast vector, must sum to zero. |
w |
A weight vector, must sum to one and contain non-negative values. |
alpha |
Confidence level, default set to 0.05. |
data |
A data frame; if provided, y, b, and z should be column names in the data frame. |
Value
IBDInfer
returns an object of class "IBD", which is a list containing the following components: :
tau.ht |
The Horvitz-Thompson estimator of tau. |
tau.haj |
The Hajek estimator of tau. |
var_tau_ht_bb |
Variance estimator for the Horvitz-Thompson estimator with between-block bias. |
var_tau_ht_wb |
Variance estimator for the Horvitz-Thompson estimator with within-block bias. |
var_tau_haj_bb |
Variance estimator for the Hajek estimator with between-block bias. |
var_tau_haj_wb |
Variance estimator for the Hajek estimator with within-block bias. |
CI_ht_bb |
Confidence interval with the Horvitz-Thompson estimator and variance estimator with between-block bias. |
CI_ht_wb |
Confidence interval with the Horvitz-Thompson estimator and variance estimator with within-block bias. |
CI_haj_bb |
Confidence interval with the Hajek estimator and variance estimator with between-block bias. |
CI_haj_wb |
Confidence interval with the Hajek estimator and variance estimator with within-block bias. |
yht |
The Horvitz-Thompson estimator for each treatment. |
yhaj |
The Hajek estimator for each treatment. |
Sht_bb |
Covariance estimator for the Horvitz-Thompson estimator for each treatment with between-block bias. |
Sht_wb |
Covariance estimator for the Horvitz-Thompson estimator for each treatment with within-block bias. |
Shaj_bb |
Covariance estimator for the Hajek estimator for each treatment with between-block bias. |
Shaj_wb |
Covariance estimator for the Hajek estimator for each treatment with within-block bias. |
alpha |
Confidence level |
References
Koo, T., Pashley, N.E. (2024), Design-based Causal Inference for Incomplete Block Designs, arXiv preprint arXiv:2405.19312.
Examples
K <- 6
n.trt <- 3
t <- 2
n.vec <- rep(4, K)
df <- IBDgen(K = K, n.trt = n.trt, t = t, n.vec = n.vec)$blk_assign
df$y <- rnorm(nrow(df), 0, 1)
IBDInfer <- IBDInfer(y = y, b = blk_id, z = assign, g = c(1, -1, 0), w = "Block", data = df)