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subtee
View on CRAN: Click
here
Download and install subtee package within the R console
Install from CRAN:
install.packages("subtee")
Install from Github:
library("remotes")
install_github("cran/subtee")
Install by package version:
library("remotes")
install_version("subtee", "1.0.1")
Attach the package and use:
library("subtee")
Maintained by
Nicolas Ballarini
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-12-21
Latest Update: 2024-02-01
Description:
Naive and adjusted treatment effect estimation for subgroups. Model
averaging (Bornkamp et.al, 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. For details, see Ballarini et.al. (2021) .
How to cite:
Nicolas Ballarini (2018). subtee: Subgroup Treatment Effect Estimation in Clinical Trials. R package version 1.0.1, https://cran.r-project.org/web/packages/subtee. Accessed 03 Dec. 2024.
Previous versions and publish date:
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Other R packages that subtee depends,
imports, suggests or enhances
Functions, R codes and Examples using
the subtee R package
Some associated functions: bagged . confint.subtee . dat . get_prca_data . modav . plot.subtee . subbuild . summary.subtee . unadj .
Some associated R codes: bagged.R . fitMods.R . generic-funcs-subtee-add.R . generic-funcs-subtee.R . get_prca_data.R . input-checking.R . mixNorm.R . modav.R . plot-funcs.R . subbuild.R . Full subtee package functions and examples
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