sim_gs_n() is available (#268, thanks to @LittleBeannie).sim_gs_n() (#273, thanks to @LittleBeannie).sim_pw_surv() and passed into the wlr() test (#281, #285 thanks to @LittleBeannie and @jdblischak).summary() is rewritten from tibble or data.frame to data.table, which is optimized to use as little memory as possible by avoiding making unnecessary temporary copies of data frames. This results in code that is more efficient in both time and memory use. (#289, thanks to @jdblischak).sim_fixed_n() function has been updated to allow parallel simulations (#249, #252, #253, #262, thanks to @cmansch and @jdblischak).wlr() function is enhanced to S3 generic to accept both counting process and time-to-event data as its input (#276, #277, thanks to @jdblischak).summary() is added (#282, thanks to @jdblischak).noSuggests checks by running code examples, tests, and vignettes
conditionally if the Suggests dependencies are not installed (#243).rmst() introduces the RMST test (#188, thanks, @LittleBeannie).milestone() introduces the milestone test
(#199, #204, #211, #237, thanks, @LittleBeannie).sim_gs_n() provides an experimental implementation for fixed sample size
group sequential design simulation, with unit tests upcoming
(#195, #201, #208, #212, thanks, @LittleBeannie and @jdblischak).create_cut() allows users to create custom interim and final
analyses cuttings based on their specific requirements
(#201, #221, thanks, @jdblischak).create_test() enables users to create various testing approaches for
interim and final analyses (#215, #221, thanks, @jdblischak).multitest() gives users the option to perform multiple tests on a
simulated dataset (#215, thanks, @jdblischak).
Note: This function is still experimental and may be improved in
future releases, as it was created prior to the standardization of
test functions in #227.early_zero() under stratified designs
(#233, thanks, @LittleBeannie).get_analysis_date() (#186, thanks, @LittleBeannie).This release makes minor improvements on auxiliary code with side-effects.
options() within vignette("modest-wlrt").tempdir() instead of the package directory.This release introduces significant changes to the API, improves simulation performance substantially, and adds new features and documentation.
sim_fixed_n() now utilizes the %dofuture% operator for parallelization,
enhancing flexibility and reproducibility (thanks, @cmansch, #110).rpwexp() adopts the inverse CDF method for random number generation,
with the naive methods now as internal functions
(thanks, @jianxiaoyang, #15 and #174).sim_fixed_n() is optimized to skip Breslow's method in the absence of ties
(thanks, @jdblischak, #130).wlr_z_stat() (thanks, @elong0527, #105).early_zero_weight() is added as a weighting function for early data removal
(thanks, @LittleBeannie, #123).get_analysis_date() is added to calculate interim/final analysis dates
under various conditions (thanks, @LittleBeannie, #122).vignette("workflow") providing an overview of data manipulations
involved in TTE simulations (thanks, @keaven, #99).vignette("parallel") demonstrating the parallelization workflow and
coding best practices (thanks, @cmansch, #113 and #134).GitHub release in February 2023.
This is the version that enables parallel computation in simfix().
GitHub release in May 2022.
This version supports the Biometrical Journal paper "A unified framework for weighted parametric group sequential design (WPGSD)" by Keaven M. Anderson, Zifang Guo, Jing Zhao, and Linda Z. Sun.
Internal development release in August 2020.
Internal development release in February 2020.
wMB() to compute Magirr-Burman weights.Depends with Imports in DESCRIPTION.Internal development release in November 2019.
simfix(), simfix2simPWSurv(), pMaxCombo()).hgraph() with intent to put it into a release of gsDesign.