The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
The goal of adaptDiag is to simplify the process of
designing adaptive trials for diagnostic test studies. With accumulating
data in a clinical trial of a new diagnostic test compared to a
gold-standard reference, decisions can be made at interim analyses to
either stop the trial for early success, stop the trial for expected
futility, or continue to the next sample size look. Designs can be
focused around test sensitivity, specificity, or both. The package is
heavily influenced by the seminal article by Broglio et al. (2014).
Broglio KR, Connor JT, Berry SM. Not too big, not too small: a Goldilocks approach to sample size selection. Journal of Biopharmaceutical Statistics, 2014; 24(3): 685–705.
You can install the development version of adaptDiag GitHub with:
# install.packages("devtools")
devtools::install_github("graemeleehickey/adaptDiag")These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.