subtee (0.3-5)

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Subgroup Treatment Effect Estimation in Clinical Trials.

Naive and adjusted treatment effect estimation for subgroups. Model averaging (Bornkamp, 2016 ) and bagging (Rosenkranz, 2016 ) are proposed to address the problem of selection bias in treatment effect estimates for subgroups. The package can be used for all commonly encountered type of outcomes in clinical trials (continuous, binary, survival, count). Additional functions are provided to build the subgroup variables to be used and to plot the results using forest plots.

Maintainer: Nicolas Ballarini
Author(s): Nicolas Ballarini [aut, cre], Bjoern Bornkamp [aut], Marius Thomas [aut, cre], Baldur Magnusson [ctb]

License: GPL-2

Uses: ggplot2, MASS, matrixStats, survival, knitr

Released 10 months ago.

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