balance_measures {aggTrees}

Balance Measures

Description

Compute several balance measures to check whether the covariate distributions are balanced across treatment arms.

Usage

balance_measures(X, D)

Arguments

X

Covariate matrix (no intercept).

D

Treatment assignment vector.

Details

For each covariate in X, balance_measures computes sample averages and standard deviations for both treatment arms. Additionally, two balance measures are computed:

Norm. Diff.

Normalized differences, computed as the differences in the means of each covariate across treatment arms, normalized by the sum of the within-arm variances. They provide a measure of the discrepancy between locations of the covariate distributions across treatment arms.

Log S.D.

Log ratio of standard deviations are computed as the logarithm of the ratio of the within-arm standard deviations. They provide a measure of the discrepancy in the dispersion of the covariate distributions across treatment arms.

Compilation of the LATEX code requires the following packages: booktabs, float, adjustbox.

Value

Prints LATEX code in the console.

Author(s)

Elena Dal Torrione, Riccardo Di Francesco

Examples

## Generate data.
set.seed(1986)

n <- 1000
k <- 3

X <- matrix(rnorm(n * k), ncol = k)
colnames(X) <- paste0("x", seq_len(k))
D <- rbinom(n, size = 1, prob = 0.5)
mu0 <- 0.5 * X[, 1]
mu1 <- 0.5 * X[, 1] + X[, 2]
y <- mu0 + D * (mu1 - mu0) + rnorm(n)

## Print table.
balance_measures(X, D)