Block Design for Response-Adaptive Randomization

Computes power for response-adaptive randomization with a block design that captures both the time and treatment effect. T. Chandereng, R. Chappell (2019) .

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Authors: Thevaa Chandereng and Rick Chappell


Response-Adaptive Randomization (RAR) is an adaptive trial where the randomization ratio of the patient changes based on the performance of the control and experimental treatment. However, most design complete ignores the time trend aspect in this design and the randomization ratio are altered based on a patient outcome. blockRAR assigns patient in a block (group) manner and the the block results are analyzed before the randomization ratio is altered. Time is divided into factor level in each block (group). The treatment effect is obtained upon adjusting for the time effect in this design. The blockRAR website is available here.


Prior to analyzing your data, the R package needs to be installed.

The easiest way to install blockRAR is through CRAN:


There are other additional ways to download blockRAR. The first option is most useful if want to download a specific version of blockRAR (which can be found at

devtools::install_github("thevaachandereng/[email protected]")
# OR 
devtools::install_version("blockRAR", version = "x.x.x", repos = "")

The second option is to download through GitHub.


After successful installation, the package must be loaded into the working space:



See the vignette for usage instructions.


If you use blockRAR, please cite:

Chandereng, T., & Chappell, R. (2019). Robust Response-Adaptive Randomization Design. arXiv preprint arXiv:1904.07758.


blockRAR is available under the open source MIT license.


Reference manual

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1.0.2 by Thevaa Chandereng, a year ago

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Browse source code at

Authors: Thevaa Chandereng [aut, cre, cph] , Rick Chapppell [aut, cph]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports dplyr, magrittr, ldbounds, tibble, methods, arm

Suggests testthat, rmarkdown, pkgdown, devtools, ggplot2, knitr

See at CRAN