log_ratio_sd

Computes a measure of the difference in the dispersion of the
covariate distributions across treatment arms.

internal

Nonparametric data-driven approach to discovering heterogeneous subgroups in a selection-on-observables framework.
'aggTrees' allows researchers to assess whether there exists relevant heterogeneity in treatment effects by generating a sequence of optimal groupings,
one for each level of granularity. For each grouping, we obtain point estimation and inference about the group average treatment effects.
Please reference the use as Di Francesco (2022) <doi:10.2139/ssrn.4304256>.

Riccardo Di Francesco

aggTrees

Aggregation Trees

log_ratio_sd function

<dl><dt>X</dt>
<dd>Covariate matrix (no intercept).</dd>
<dt>D</dt>
<dd>Treatment assignment vector.</dd></dl>

Arguments

Log Ratio of Standard Deviations — log_ratio_sd

<dl>

<dt>X</dt>
<dd>Covariate matrix (no intercept).</dd>


<dt>D</dt>
<dd>Treatment assignment vector.</dd>

</dl>

log_ratio_sd: Log Ratio of Standard Deviations

Description

Usage

Value

Arguments

Details