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Decision Tree Analysis for Probabilistic Subgroup Identification with Multiple Treatments

Installation

About

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.

Citation psica citation info

Key Metrics

Version 1.0.2
Published 2020-02-11 1538 days ago
Needs compilation? no
License GPL-2
License GPL-3
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Maintainer

Maintainer

Oleg Sysoev

Oleg.Sysoev@liu.se

Authors

Oleg Sysoev
Krzysztof Bartoszek
Katarina Ekholm Selling
Lotta Ekstrom

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

psica archive

Imports

Rdpack
grid
gridBase
randomForest
rpart
partykit
party
BayesTree