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subtee  

Subgroup Treatment Effect Estimation in Clinical Trials
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]
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
Previous versions and publish date:
0.3-3 (2018-12-21 14:50), 0.3-4 (2019-01-07 17:40), 0.3-5 (2019-04-22 18:00), 0.3-6 (2020-09-03 09:30), 0.3-7.1 (2021-02-25 12:10), 1.0.0 (2021-10-25 18:20), 1.0.1 (2022-03-22 15:10)
Other packages that cited subtee R package
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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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