# model4you v0.9-5

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## 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) <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>.

## Functions in model4you

Name | Description | |

binomial_glm_plot | Plot for a given logistic regression model (glm with binomial family) with one binary covariate. | |

logLik.pmtree | Extract log-Likelihood | |

coxph_plot | Survival plot for a given coxph model with one binary covariate. | |

lm_plot | Density plot for a given lm model with one binary covariate. | |

.prepare_args | Prepare input for ctree/cforest from input of pmtree/pmforest | |

.modelfit | Fit function when model object is given | |

node_pmterminal | Panel-Generator for Visualization of pmtrees | |

objfun | Objective function | |

.add_modelinfo | Add model information to a personalised-model-ctree | |

coeftable.survreg | Table of coefficients for survreg model | |

pmtree | Compute model-based tree from model. | |

one_factor | Check if model has only one factor covariate. | |

pmforest | Compute model-based forest from model. | |

predict.pmtree | pmtree predictions | |

objfun.pmodel_identity | Objective function of personalised models | |

print.pmtree | Methods for pmtree | |

survreg_plot | Survival plot for a given survreg model with one binary covariate. | |

pmodel | Personalised model | |

pmtest | Test if personalised models improve upon base model. | |

varimp.pmforest | Variable Importance for pmforest | |

objfun.pmtree | Objective function of a given pmtree | |

rss | Residual sum of squares | |

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## Details

Date | 2020-02-12 |

License | GPL-2 | GPL-3 |

Encoding | UTF-8 |

RoxygenNote | 6.1.1 |

NeedsCompilation | no |

Packaged | 2020-02-17 10:27:40 UTC; kennwortistkennwort |

Repository | CRAN |

Date/Publication | 2020-02-19 09:20:02 UTC |

imports | Formula , ggplot2 , gridExtra , methods , sandwich , stats , survival |

suggests | ggbeeswarm , knitr , MASS , mvtnorm , plyr , psychotools , strucchange , TH.data |

depends | grid , partykit (>= 1.2-6) , R (>= 3.1.0) |

Contributors | Achim Zeileis, Torsten Hothorn |

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