balance_measures {aggTrees} | R Documentation |

## 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)
```

*aggTrees*version 2.0.2 Index]