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model4you
View on CRAN: Click
here
Download and install model4you package within the R console
Install from CRAN:
install.packages("model4you")
Install from Github:
library("remotes")
install_github("cran/model4you") Install by package version:
library("remotes")
install_version("model4you", "0.9-9") Attach the package and use:
library("model4you")
Maintained by
Heidi Seibold
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-01-16
Latest Update: 2024-11-08
Description:
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) .
How to cite:
Heidi Seibold (2018). model4you: Stratified and Personalised Models Based on Model-Based Trees and Forests. R package version 0.9-9, https://cran.r-project.org/web/packages/model4you. Accessed 09 Mar. 2026.
Previous versions and publish date:
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Complete documentation for model4you
Functions, R codes and Examples using
the model4you R package
Some associated functions: binomial_glm_plot . coeftable.survreg . coxph_plot . dot-add_modelinfo . dot-modelfit . dot-prepare_args . lm_plot . logLik.pmtree . node_pmterminal . objfun . objfun.pmodel_identity . objfun.pmtree . one_factor . pmforest . pmodel . pmtest . pmtree . predict.pmtree . print.pmtree . rss . survreg_plot . varimp.pmforest .
Some associated R codes: helpers.R . objfun.R . plot-pmtree.R . pmforest.R . pmodel-methods.R . pmodel-test.R . pmodel.R . pmtree-methods.R . pmtree.R . varimp.R . Full model4you package functions and examples
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