RARtrials
Response-Adaptive Randomization in Clinical Trials
Some response-adaptive randomization methods commonly found in literature are included in this package. These methods include the randomized play-the-winner rule for binary endpoint (Wei and Durham (1978)), the doubly adaptive biased coin design with minimal variance strategy for binary endpoint (Atkinson and Biswas (2013), Rosenberger and Lachin (2015)) and maximal power strategy targeting Neyman allocation for binary endpoint (Tymofyeyev, Rosenberger, and Hu (2007)) and RSIHR allocation with each letter representing the first character of the names of the individuals who first proposed this rule (Youngsook and Hu (2010), Bello and Sabo (2016)), A-optimal Allocation for continuous endpoint (Sverdlov and Rosenberger (2013)), Aa-optimal Allocation for continuous endpoint (Sverdlov and Rosenberger (2013)), generalized RSIHR allocation for continuous endpoint (Atkinson and Biswas (2013)), Bayesian response-adaptive randomization with a control group using the Thall & Wathen method for binary and continuous endpoints (Thall and Wathen (2007)) and the forward-looking Gittins index rule for binary and continuous endpoints (Villar, Wason, and Bowden (2015), Williamson and Villar (2019)).
- Version0.0.1
- R version≥ 4.3 stats,
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release06/04/2024
Documentation
Team
Chuyao Xu
Thomas Lumley
Show author detailsRolesAuthor, Thesis advisorAlain Vandal
Show author detailsRolesAuthor, Thesis advisorSofia S. Villar
Show author detailsRolesCopyright holderKyle J. Wathen
Show author detailsRolesCopyright holder
Insights
Last 30 days
This package has been downloaded 121 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,336 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 21, 2024 with 65 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends1 package
- Imports1 package
- Suggests3 packages