## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(SMARTbayesR) ## ----------------------------------------------------------------------------- set.seed(23856) dat <- SimDesign1(sample_size = 250, response_prob = c(0.2,0.3,0.4,0.5,0.6,0.7), stage_one_trt_one_response_prob = 0.7, stage_one_trt_two_response_prob = 0.4) ## ----------------------------------------------------------------------------- set.seed(39864) posterior_trt_seq_draws <- PosteriorTrtSeqProb(niter = 10000, dat, design = "design-1") ## ----------------------------------------------------------------------------- posterior_EDTR_draws <- PosteriorEDTRProbs(posterior_trt_seq_draws) ## ----------------------------------------------------------------------------- MCBUpperLimits(thetadraws=posterior_EDTR_draws, alpha=0.05, design="design-1", type="log-OR") ## ----------------------------------------------------------------------------- LogOR(response_prob = c(0.3,0.3,0.3,0.8,0.6,0.7), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, design = "design-1") ## ---- results="hide"---------------------------------------------------------- set.seed(2364) power1 <- PowerBayesian("design-1", sample_size = 100, response_prob = c(0.2,0.3,0.4,0.5,0.6,0.7), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, type="log-OR", threshold=1) ## ----------------------------------------------------------------------------- power1 ## ----------------------------------------------------------------------------- LogRR(response_prob = c(0.3,0.3,0.3,0.8,0.6,0.7), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, design = "design-1") ## ---- results="hide"---------------------------------------------------------- set.seed(23641) power2 <- PowerBayesian("design-1", sample_size = 100, response_prob = c(0.2,0.3,0.4,0.5,0.6,0.7), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, type="log-RR", threshold=0.8) ## ----------------------------------------------------------------------------- power2 ## ----------------------------------------------------------------------------- RD(response_prob = c(0.3,0.3,0.3,0.8,0.6,0.7), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, design = "design-1") ## ---- results="hide"---------------------------------------------------------- set.seed(236412) power3 <- PowerBayesian("design-1", sample_size = 100, response_prob = c(0.2,0.3,0.4,0.5,0.6,0.7), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, type="RD", threshold=0.3) ## ----------------------------------------------------------------------------- power3 ## ----------------------------------------------------------------------------- LogOR(response_prob = c(0.2,0.3,0.4,0.5,0.6,0.7,0.7,0.6), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, design = "general") ## ---- results="hide"---------------------------------------------------------- set.seed(23644) power4 <- PowerBayesian("general", sample_size = 250, response_prob = c(0.2,0.3,0.4,0.5,0.6,0.7,0.7,0.6), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, type="log-OR", threshold=1) ## ----------------------------------------------------------------------------- power4 ## ----------------------------------------------------------------------------- LogOR(response_prob = c(0.2,0.3,0.4,0.5,0.6,0.7,0.7,0.6,0.9), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, stage_one_trt_three_response_prob = 0.7, design = "design-3") ## ---- results="hide"---------------------------------------------------------- set.seed(236445) power5 <- PowerBayesian("design-3", sample_size = 250, response_prob = c(0.2,0.3,0.4,0.5,0.6,0.7,0.7,0.6,0.9), stage_one_trt_one_response_prob = 0.6, stage_one_trt_two_response_prob = 0.4, stage_one_trt_three_response_prob = 0.7, type="log-OR", threshold=0.8) ## ----------------------------------------------------------------------------- power5