Stratified and Personalised Models Based on Model-Based Trees and Forests

Model-based trees for subgroup analyses in clinical trials and model-based forests for the estimation and prediction of personalised treatment effects (personalised models). Currently partitioning of linear models, lm(), generalised linear models, glm(), and Weibull models, survreg(), is supported. Advanced plotting functionality is supported for the trees and a test for parameter heterogeneity is provided for the personalised models. For details on model-based trees for subgroup analyses see Seibold, Zeileis and Hothorn (2016) ; for details on model-based forests for estimation of individual treatment effects see Seibold, Zeileis and Hothorn (2017) .


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0.9-7 by Heidi Seibold, 10 months ago

Browse source code at

Authors: Heidi Seibold [aut, cre] , Achim Zeileis [aut] , Torsten Hothorn [aut]

Documentation:   PDF Manual  

Task views:

GPL-2 | GPL-3 license

Imports sandwich, stats, methods, ggplot2, Formula, gridExtra, survival

Depends on partykit, grid

Suggests mvtnorm,, psychotools, strucchange, plyr, knitr, ggbeeswarm, MASS

See at CRAN