Decision Tree Analysis for Probabilistic Subgroup Identification with Multiple Treatments

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.


Reference manual

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1.0.2 by Oleg Sysoev, 2 years ago

Browse source code at

Authors: Oleg Sysoev , Krzysztof Bartoszek , Katarina Ekholm Selling and Lotta Ekstrom

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rdpack, grid, gridBase, randomForest, rpart, partykit, party, BayesTree

See at CRAN