Implements the Goldilocks adaptive trial design for a time to event outcome using a piecewise exponential model and conjugate Gamma prior distributions. The method closely follows the article by Broglio and colleagues <doi:10.1080/10543406.2014.888569>, which allows users to explore the operating characteristics of different trial designs.
| Version: | 0.4.0 |
| Depends: | R (≥ 3.6.0),survival |
| Imports: | dplyr, parallel,pbmcapply,PWEALL,Rcpp,rlang, stats |
| LinkingTo: | BH,Rcpp |
| Suggests: | covr,testthat (≥ 3.0.0),knitr,rmarkdown |
| Published: | 2025-01-08 |
| DOI: | 10.32614/CRAN.package.goldilocks |
| Author: | Graeme L. Hickey [aut, cre], Ying Wan [aut], Thevaa Chandereng [aut] (bayesDP code as a template), Becton, Dickinson and Company [cph], Tim Kacprowski [ctb] (For code from fastlogrank R package.) |
| Maintainer: | Graeme L. Hickey <graemeleehickey at gmail.com> |
| BugReports: | https://github.com/graemeleehickey/goldilocks/issues |
| License: | GPL-3 |
| URL: | https://github.com/graemeleehickey/goldilocks |
| NeedsCompilation: | yes |
| Language: | en-US |
| Materials: | README,NEWS |
| CRAN checks: | goldilocks results |