goldilocks: Goldilocks Adaptive Trial Designs for Time-to-Event Endpoints

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: 0.3.0
Depends: R (≥ 3.6.0), survival
Imports: dplyr, fastlogranktest, parallel, pbmcapply, PWEALL, rlang, stats
Suggests: covr, testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2021-05-10
Author: Graeme L. Hickey ORCID iD [aut, cre], Ying Wan [aut], Thevaa Chandereng ORCID iD [aut] (bayesDP code as a template), Becton, Dickinson and Company [cph]
Maintainer: Graeme L. Hickey <graemeleehickey at gmail.com>
License: GPL-3
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: goldilocks results

Documentation:

Reference manual: goldilocks.pdf
Vignettes: Example: Two-armed RCT

Downloads:

Package source: goldilocks_0.3.0.tar.gz
Windows binaries: r-devel: goldilocks_0.3.0.zip, r-release: goldilocks_0.3.0.zip, r-oldrel: goldilocks_0.3.0.zip
macOS binaries: r-release (arm64): goldilocks_0.3.0.tgz, r-oldrel (arm64): goldilocks_0.3.0.tgz, r-release (x86_64): goldilocks_0.3.0.tgz, r-oldrel (x86_64): goldilocks_0.3.0.tgz

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