Getting Started with `impart`

There are several excellent resources available to provide both background on group sequential design methods and examples of planning and analyses using R:

• The rpact package for group sequential designs
  • rpact vignettes
• The gsDesign package for group sequential designs
  • Group Sequential Designs Made Easy by Keaven Anderson and Nan Xiao

Since group sequential design methodology can also implemented in information monitoring trials, users should understand the fundamentals of these designs.

Using impart

There are several vignettes built into impart: these include vignettes on information monitoring designs as well as group sequential designs. To see all available vignettes in impart, use the vignettes command:

print(vignette(package = "impart"))
#> no vignettes found

If you are using impart in practice, please

citation(package = "impart")
#> To cite package 'impart' in publications use:
#> 
#>   Van Lancker K, Betz J, Rosenblum M (2024). _impart: Information
#>   Monitoring for Precision Adaptive Randomized Trials_. R package
#>   version 0.1.0, https://github.com/jbetz-jhu/impart,
#>   <https://jbetz-jhu.github.io/impart/>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {impart: Information Monitoring for Precision Adaptive Randomized Trials},
#>     author = {Kelly {Van Lancker} and Josh Betz and Michael Rosenblum},
#>     year = {2024},
#>     note = {R package version 0.1.0, 
#> https://github.com/jbetz-jhu/impart},
#>     url = {https://jbetz-jhu.github.io/impart/},
#>   }