Decision Tree Analysis for Probabilistic Subgroup Identification with Multiple Treatments
Overview
In the situation when multiple alternative treatments or interventions available, different population groups may respond differently to different treatments. This package implements a method that discovers the population subgroups in which a certain treatment has a better effect than the other alternative treatments. This is done by first estimating the treatment effect for a given treatment and its uncertainty by computing random forests, and the resulting model is summarized by a decision tree in which the probabilities that the given treatment is best for a given subgroup is shown in the corresponding terminal node of the tree.
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Maintainer: ‘Oleg Sysoev <Oleg.Sysoev@liu.se>’
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Documentation
- Help pages
- 6
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
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- Documented parameters
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- Return-value docs
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- Help pages citing references
- 17% with a bibliography file
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Maintainer since 1.0.0 (2018)
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 1.0.2Latest
- RR 3.6.0 released · 2019-04-26
- 1.0.12018-11-29 · diff ↗
- 1.0.02018-11-19
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-11-19
- Total releases
- 3 / 8 yrs
- License
- GPL (>= 2) OSI
- Download size
- 17 KB
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