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aggTrees: Aggregation Trees
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>.
Getting started
Browse package contents
Package details |
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| Author | Riccardo Di Francesco [aut, cre, cph] |
| Maintainer | Riccardo Di Francesco <difrancesco.riccardo96@gmail.com> |
| License | MIT + file LICENSE |
| Version | 2.1.0 |
| URL | https://riccardo-df.github.io/aggTrees/ |
| Package repository | View on CRAN |
| Installation |
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