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goldilocks  

Adaptive Trial Designs for Survival and Binary Endpoints
View on CRAN: Click here


Download and install goldilocks package within the R console
Install from CRAN:
install.packages("goldilocks")

Install from Github:
library("remotes")
install_github("cran/goldilocks")

Install by package version:
library("remotes")
install_version("goldilocks", "1.0.0")



Attach the package and use:
library("goldilocks")
Maintained by
Graeme L. Hickey
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-10
Latest Update: 2025-01-08
Description:
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 , which allows users to explore the operating characteristics of different trial designs.
How to cite:
Graeme L. Hickey (2021). goldilocks: Adaptive Trial Designs for Survival and Binary Endpoints. R package version 1.0.0, https://cran.r-project.org/web/packages/goldilocks. Accessed 06 Oct. 2026.
Previous versions and publish date:
(2026-09-09 16:40), 0.3.0 (2021-05-10 10:20), 0.4.0 (2025-01-08 16:30), 0.5.0 (2026-06-10 08:10), 0.6.0 (2026-07-29 19:00)
Other packages that cited goldilocks R package
View goldilocks citation profile
Other R packages that goldilocks depends, imports, suggests or enhances
Complete documentation for goldilocks
Functions, R codes and Examples using the goldilocks R package
Some associated functions: enrollment . goldilocks . ppwe . prop_to_haz . pwe_impute . pwe_sim . randomization . sim_trials . summarise_sims . survival_adapt . 
Some associated R codes: analyse_data.R . enrollment.R . goldilocks.R . haz_to_prop.R . impute_data.R . posterior.R . prop_to_haz.R . pwe.R . randomization.R . sim_trials.R . summarise_sims.R . survival_adapt.R .  Full goldilocks package functions and examples
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