## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----------------------------------------------------------------------------- library(drugdevelopR) ## ----eval = FALSE------------------------------------------------------------- # res <- optimal_tte(w = 0.3, # define parameters for prior # hr1 = 0.75, hr2 = 0.8, id1 = 210, id2 = 420, # (https://web.imbi.uni-heidelberg.de/prior/) # d2min = 20, d2max = 400, stepd2 = 5, # define optimization set for d2 # hrgomin = 0.7, hrgomax = 0.9, stephrgo = 0.01, # define optimization set for HRgo # alpha = 0.025, beta = 0.1, xi2 = 0.7, xi3 = 0.7, # drug development planning parameters # c2 = 0.75, c3 = 1, c02 = 100, c03 = 150, # define fixed and variable costs # K = Inf, N = Inf, S = -Inf, # set constraints # steps1 = 1, stepm1 = 0.95, stepl1 = 0.85, # define boundary for effect size categories # b1 = 1000, b2 = 2000, b3 = 3000, # define expected benefits # gamma = 0, # assume different/same population structures # fixed = TRUE, # choose if effects are fixed or random # skipII = FALSE, # more parameters # num_cl = 1) ## ----eval=TRUE, include=FALSE------------------------------------------------- # Comment this chunk after running it once # res <- optimal_tte(w = 0.3, # define parameters for prior # hr1 = 0.75, hr2 = 0.8, id1 = 210, id2 = 420, # (https://web.imbi.uni-heidelberg.de/prior/) # d2min = 20, d2max = 400, stepd2 = 5, # define optimization set for d2 # hrgomin = 0.7, hrgomax = 0.9, stephrgo = 0.01, # define optimization set for HRgo # alpha = 0.025, beta = 0.1, xi2 = 0.7, xi3 = 0.7, # drug development planning parameters # c2 = 0.75, c3 = 1, c02 = 100, c03 = 150, # define fixed and variable costs # K = Inf, N = Inf, S = -Inf, # set constraints # steps1 = 1, stepm1 = 0.95, stepl1 = 0.85, # define boundary for effect size categories # b1 = 1000, b2 = 2000, b3 = 3000, # define expected benefits # gamma = 0, # assume different/same population structures # fixed = TRUE, # choose if effects are fixed or random # skipII = FALSE, # more parameters # num_cl = 1) # saveRDS(res, file="optimal_tte_basic_setting.RDS") ## ----eval=TRUE, include=FALSE------------------------------------------------- res <- readRDS(file="optimal_tte_basic_setting.RDS") ## ----------------------------------------------------------------------------- res