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) <doi:10.1515/ijb-2015-0032>; for details on model-based forests for estimation of individual treatment effects see Seibold, Zeileis and Hothorn (2017) <doi:10.1177/0962280217693034>.
|Author||Heidi Seibold [aut, cre], Achim Zeileis [aut], Torsten Hothorn [aut]|
|Maintainer||Heidi Seibold <[email protected]>|
|License||GPL-2 | GPL-3|
|Package repository||View on R-Forge|
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