Package: WCRBayesDesign 1.0.1
WCRBayesDesign: Bayesian Two-Stage Design with Window-Cohort and Controlled Roll-on for Time-to-Event Estimand
Calibrates Bayesian two-stage designs for single-arm phase II trials with time-to-event endpoints using a window-cohort with controlled roll-on. Interim monitoring is anchored to a locked interim cohort and a pre-specified follow-up requirement, so analysis timing remains predictable while preserving follow-up maturity. The package searches feasible interim rules, optimizes final sample size and decision thresholds, evaluates operating characteristics by Monte Carlo simulation, and supports exponential, Weibull, log-normal, log-logistic, and user-defined baseline survival models. Related published foundations include Simon (1989) <doi:10.1016/0197-2456(89)90015-9> and Cotterill and Whitehead (2015) <doi:10.1002/sim.6426>.
Authors:
WCRBayesDesign_1.0.1.tar.gz
WCRBayesDesign_1.0.1.zip(r-4.7)WCRBayesDesign_1.0.1.zip(r-4.6)WCRBayesDesign_1.0.1.zip(r-4.5)
WCRBayesDesign_1.0.1.tgz(r-4.6-any)WCRBayesDesign_1.0.1.tgz(r-4.5-any)
WCRBayesDesign_1.0.1.tar.gz(r-4.7-any)WCRBayesDesign_1.0.1.tar.gz(r-4.6-any)
WCRBayesDesign_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
WCRBayesDesign/json (API)
| # Install 'WCRBayesDesign' in R: |
| install.packages('WCRBayesDesign', repos = c('https://zhongheng-biostatistics.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:f0a04f9843. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 135 | ||
| source / vignettes | OK | 175 | ||
| linux-release-x86_64 | OK | 124 | ||
| macos-release-arm64 | OK | 84 | ||
| macos-oldrel-arm64 | OK | 72 | ||
| windows-devel | OK | 89 | ||
| windows-release | OK | 86 | ||
| windows-oldrel | OK | 72 | ||
| wasm-release | OK | 111 |
Exports:conductdelta_from_theta_goalfind_Nw_pIAoc_two_stagerun_two_stage_trialS0_inverseS0_weibullstats_transformedtwo_stage_optimize_design
Dependencies:codetoolsdoParallelforeachiterators
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian Interim and Final Analysis (Unified Transformed Time Framework) | conduct |
| Convert target EFS goal to delta parameter under proportional hazards model | delta_from_theta_goal |
| Search for feasible interim analysis thresholds (Unified Framework) | find_Nw_pIA |
| Evaluate operating characteristics for two-stage adaptive survival designs (Unified Framework) | oc_two_stage |
| Run Two-Stage Bayesian Single-Arm Survival Trial Simulation | run_two_stage_trial |
| Inverse of baseline survival function S_0 | S0_inverse |
| Weibull reference survival function | S0_weibull |
| Compute transformed statistics for survival data | stats_transformed |
| Optimize two-stage adaptive survival design | two_stage_optimize_design |
