## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(drugdevelopR) ## ----eval=TRUE, include=FALSE------------------------------------------------- res <- readRDS(file="optimal_normal_basic_setting.RDS") ## ----------------------------------------------------------------------------- res ## ----eval = FALSE------------------------------------------------------------- # resK <- optimal_normal(Delta1 = 0.625, fixed = TRUE, # treatment effect # n2min = 20, n2max = 400, # sample size region # stepn2 = 4, # sample size step size # kappamin = 0.02, kappamax = 0.2, # threshold region # stepkappa = 0.02, # threshold step size # c2 = 0.675, c3 = 0.72, # maximal total trial costs # c02 = 15, c03 = 20, # maximal per-patient costs # b1 = 3000, b2 = 8000, b3 = 10000, # gains for patients # alpha = 0.025, # one-sided significance level # beta = 0.1, # 1 - power # Delta2 = NULL, w = NULL, in1 = NULL, in2 = NULL, # a = NULL,b = NULL, # setting all unneeded parameters to NULL # K = 200 # cost constraint # ) ## ----eval=TRUE, include=FALSE------------------------------------------------- # Comment this chunk after running it once # resK <- optimal_normal(Delta1 = 0.625, fixed = TRUE, # treatment effect # n2min = 20, n2max = 400, # sample size region # stepn2 = 4, # sample size step size # kappamin = 0.02, kappamax = 0.2, # threshold region # stepkappa = 0.02, # threshold step size # c2 = 0.675, c3 = 0.72, # maximal total trial costs # c02 = 15, c03 = 20, # maximal per-patient costs # b1 = 3000, b2 = 8000, b3 = 10000, # gains for patients # alpha = 0.025, # significance level # beta = 0.1, # 1 - power # Delta2 = NULL, w = NULL, in1 = NULL, in2 = NULL, # a = NULL,b = NULL, # K = 200) # setting all unneeded parameters to NULL # saveRDS(resK, file="optimal_normal_cost_constraint.RDS") ## ----eval=TRUE, include=FALSE------------------------------------------------- resK <- readRDS(file="optimal_normal_cost_constraint.RDS") ## ----------------------------------------------------------------------------- resK ## ----eval = FALSE------------------------------------------------------------- # resN <- optimal_normal(Delta1 = 0.625, fixed = TRUE, # treatment effect # n2min = 20, n2max = 400, # sample size region # stepn2 = 4, # sample size step size # kappamin = 0.02, kappamax = 0.2, # threshold region # stepkappa = 0.02, # threshold step size # c2 = 0.675, c3 = 0.72, # maximal total trial costs # c02 = 15, c03 = 20, # maximal per-patient costs # b1 = 3000, b2 = 8000, b3 = 10000, # gains for patients # alpha = 0.025, # significance level # beta = 0.1, # 1 - power # Delta2 = NULL, w = NULL, in1 = NULL, in2 = NULL, # a = NULL,b = NULL, # setting all unneeded parameters to NULL # N = 200 # sample size constraint # ) ## ----eval=TRUE, include=FALSE------------------------------------------------- # Comment this chunk after running it once # resN <- optimal_normal(Delta1 = 0.625, fixed = TRUE, # treatment effect # n2min = 20, n2max = 400, # sample size region # stepn2 = 4, # sample size step size # kappamin = 0.02, kappamax = 0.2, # threshold region # stepkappa = 0.02, # threshold step size # c2 = 0.675, c3 = 0.72, # maximal total trial costs # c02 = 15, c03 = 20, # maximal per-patient costs # b1 = 3000, b2 = 8000, b3 = 10000, # gains for patients # alpha = 0.025, # significance level # beta = 0.1, # 1 - power # Delta2 = NULL, w = NULL, in1 = NULL, in2 = NULL, # a = NULL,b = NULL, # N = 200) # saveRDS(resN, file="optimal_normal_sample_size_constraint.RDS") ## ----eval=TRUE, include=FALSE------------------------------------------------- resN <- readRDS(file="optimal_normal_sample_size_constraint.RDS") ## ----------------------------------------------------------------------------- resN ## ----eval = FALSE------------------------------------------------------------- # resS <- optimal_normal(Delta1 = 0.625, fixed = TRUE, # treatment effect # n2min = 20, n2max = 400, # sample size region # stepn2 = 4, # sample size step size # kappamin = 0.02, kappamax = 0.2, # threshold region # stepkappa = 0.02, # threshold step size # c2 = 0.675, c3 = 0.72, # maximal total trial costs # c02 = 15, c03 = 20, # maximal per-patient costs # b1 = 3000, b2 = 8000, b3 = 10000, # gains for patients # alpha = 0.025, # significance level # beta = 0.1, # 1 - power # Delta2 = NULL, w = NULL, in1 = NULL, in2 = NULL, # a = NULL,b = NULL, # setting all unneeded parameters to NULL # S = 0.87 #minimum success probability # ) ## ----eval=TRUE, include=FALSE------------------------------------------------- # Comment this chunk after running it once # resS <- optimal_normal(Delta1 = 0.625, fixed = TRUE, # treatment effect # n2min = 20, n2max = 400, # sample size region # stepn2 = 4, # sample size step size # kappamin = 0.02, kappamax = 0.2, # threshold region # stepkappa = 0.02, # threshold step size # c2 = 0.675, c3 = 0.72, # maximal total trial costs # c02 = 15, c03 = 20, # maximal per-patient costs # b1 = 3000, b2 = 8000, b3 = 10000, # gains for patients # alpha = 0.025, # significance level # beta = 0.1, # 1 - power # Delta2 = NULL, w = NULL, in1 = NULL, in2 = NULL, # a = NULL,b = NULL, # S = 0.87) # setting all unneeded parameters to NULL # saveRDS(resS, file="optimal_normal_probability_constraint.RDS") ## ----eval=TRUE, include=FALSE------------------------------------------------- resS <- readRDS(file="optimal_normal_probability_constraint.RDS") ## ----------------------------------------------------------------------------- resS ## ----eval = FALSE------------------------------------------------------------- # res <- optimal_normal(Delta1 = 0.625, fixed = TRUE, # treatment effect # n2min = 20, n2max = 400, # sample size region # stepn2 = 4, # sample size step size # kappamin = 0.02, kappamax = 0.2, # threshold region # stepkappa = 0.02, # threshold step size # c2 = 0.675, c3 = 0.72, # maximal total trial costs # c02 = 15, c03 = 20, # maximal per-patient costs # b1 = 3000, b2 = 8000, b3 = 10000, # gains for patients # alpha = 0.025, # significance level # beta = 0.1, # 1 - power # Delta2 = NULL, w = NULL, in1 = NULL, in2 = NULL, # a = NULL,b = NULL, # setting all unneeded parameters to NULL # steps1 = 0.1, stepm1 = 0.6, stepl1 = 1 # step sizes for effect size categories # ) ## ----eval = FALSE------------------------------------------------------------- # resII <- optimal_normal(Delta1 = 0.625, fixed = TRUE, # treatment effect # n2min = 20, n2max = 400, # sample size region # stepn2 = 4, # sample size step size # kappamin = 0.02, kappamax = 0.2, # threshold region # stepkappa = 0.02, # threshold step size # c2 = 0.675, c3 = 0.72, # maximal total trial costs # c02 = 15, c03 = 20, # maximal per-patient costs # b1 = 3000, b2 = 8000, b3 = 10000, # gains for patients # alpha = 0.025, # significance level # beta = 0.1, # 1 - power # Delta2 = NULL, w = NULL, in1 = NULL, in2 = NULL, # a = NULL,b = NULL, # setting all unneeded parameters to NULL # skipII = TRUE #skipping phase II # ) ## ----eval=TRUE, include=FALSE------------------------------------------------- # Comment this chunk after running it once # resII <- optimal_normal(Delta1 = 0.625, fixed = TRUE, # treatment effect # n2min = 20, n2max = 400, # sample size region # stepn2 = 4, # sample size step size # kappamin = 0.02, kappamax = 0.2, # threshold region # stepkappa = 0.02, # threshold step size # c2 = 0.675, c3 = 0.72, # maximal total trial costs # c02 = 15, c03 = 20, # maximal per-patient costs # b1 = 3000, b2 = 8000, b3 = 10000, # gains for patients # alpha = 0.025, # significance level # beta = 0.1, # 1 - power # Delta2 = NULL, w = NULL, in1 = NULL, in2 = NULL, # a = NULL,b = NULL, # skipII = TRUE) # saveRDS(resII, file="optimal_normal_skipII.RDS") ## ----eval=TRUE, include=FALSE------------------------------------------------- resII <- readRDS(file="optimal_normal_skipII.RDS") ## ----------------------------------------------------------------------------- resII