Incertus.jl -- The Julia Lego Blocks for Randomized Clinical Trial Designs (2407.14248v1)
Abstract: In this paper, we present Insertus.jl, the Julia package that can help the user generate a randomization sequence of a given length for a multi-arm trial with a pre-specified target allocation ratio and assess the operating characteristics of the chosen randomization method through Monte Carlo simulations. The developed package is computationally efficient, and it can be invoked in R. Furthermore, the package is open-ended -- it can flexibly accommodate new randomization procedures and evaluate their statistical properties via simulation. It may be also helpful for validating other randomization methods for which software is not readily available. In summary, Insertus.jl can be used as ``Lego Blocks'' to construct a fit-for-purpose randomization procedure for a given clinical trial design.
Sponsored by Paperpile, the PDF & BibTeX manager trusted by top AI labs.
Get 30 days freePaper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.