Shrinkage Based Forest Plots

Subgroup analyses are routinely performed in clinical trial analyses. From a methodological perspective, two key issues of subgroup analyses are multiplicity (even if only predefined subgroups are investigated) and the low sample sizes of subgroups which lead to highly variable estimates, see e.g. Yusuf et al (1991) . This package implements subgroup estimates based on Bayesian shrinkage priors, see Carvalho et al (2019) < https://proceedings.mlr.press/v5/carvalho09a.html>. In addition, estimates based on penalized likelihood inference are available, based on Simon et al (2011) . The corresponding shrinkage based forest plots address the aforementioned issues and can complement standard forest plots in practical clinical trial analyses.


Reference manual

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install.packages("bonsaiforest")

0.1.1 by Isaac Gravestock, 2 years ago


https://github.com/insightsengineering/bonsaiforest/


Report a bug at https://github.com/insightsengineering/bonsaiforest/issues


Browse source code at https://github.com/cran/bonsaiforest


Authors: Mar Vazquez Rabunal [aut] , Daniel Sabanés Bové [aut] , Marcel Wolbers [aut] , Isaac Gravestock [cre] , F. Hoffmann-La Roche AG [cph, fnd]


Documentation:   PDF Manual  


Apache License 2.0 license


Imports brms, broom, checkmate, dplyr, forcats, gbm, ggplot2, glmnet, MASS, Rcpp, splines2, stats, survival, tibble, tidyr, tidyselect, vdiffr

Suggests knitr, rmarkdown, testthat

Linking to Rcpp, RcppArmadillo


See at CRAN