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 |