Simulate and Analyse Bayesian Platform Trial with Time Trend R package BayesianPlatformDesignTimeTrend version 1.2.3 Simulating the sequential multi-arm multi-stage or platform trial with Bayesian approach using the 'rstan' package, which provides the R interface for the Stan. This package supports fixed ratio and Bayesian adaptive randomization approaches for randomization. Additionally, it allows for the study of time trend problems in platform trials. There are demos available for a multi-arm multi-stage trial with two different null scenarios, as well as for Bayesian trial cutoff screening. The Bayesian adaptive randomisation approaches are described in: Trippa et al. (2012) <doi:10.1200/JCO.2011.39.8420> and Wathen et al. (2017) <doi:10.1177/1740774517692302>. The randomisation algorithm is described in: Zhao W <doi:10.1016/j.cct.2015.06.008>. The analysis methods of time trend effect in platform trial are described in: Saville et al. (2022) <doi:10.1177/17407745221112013> and Bofill Roig et al. (2022) <doi:10.1186/s12874-022-01683-w>. Software Depends: R (>= 4.0.0), rstan (>= 2.32.1) Imports: BiocManager (>= 1.30.19), boot (>= 1.3-28), doParallel (>= 1.0.17), foreach (>= 1.5.1), ggplot2 (>= 3.4.0), ggpubr (>= 0.4.0), iterators (>= 1.0.13), laGP (>= 1.5-9), lhs (>= 1.1.6), matrixStats (>= 0.61.0), methods, RColorBrewer (>= 1.1-3), Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), reshape (>= 0.8.8), rstantools (>= 2.3.1.1), stringr (>= 1.4.0) LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), StanHeaders (>= 2.26.0), rstan (>= 2.26.1) Suggests: rmarkdown, knitr Ziyan Wang <zw7g20@soton.ac.uk> Comprehensive R Archive Network (CRAN) Ziyan Wang [aut, cre], David Woods [ctb] MIT + file LICENSE (https://CRAN.R-project.org/package=BayesianPlatformDesignTimeTrend/LICENSE) 2023-12-07 application/tgz https://CRAN.R-project.org/package=BayesianPlatformDesignTimeTrend doi:10.32614/CRAN.package.BayesianPlatformDesignTimeTrend