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)
|Author||Heidi Seibold [aut, cre], Achim Zeileis [aut], Torsten Hothorn [aut]|
|Date of publication||2018-06-12 07:06:46|
|Maintainer||Heidi Seibold <[email protected]>|
|License||GPL-2 | GPL-3|
|Package repository||View on R-Forge|
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