## ----setup, include=FALSE, echo=FALSE----------------------------------------- library('CompAREdesign') # Load library library('ggplot2') knitr::opts_chunk$set(echo = TRUE) # Show code ## ----------------------------------------------------------------------------- ## Probabilities of observing the event in control arm during follow-up p0_e1 <- 0.59 # Death p0_e2 <- 0.74 # Disease Progression ## Effect size (Cause specific hazard ratios) for each endpoint HR_e1 <- 0.91 # Death HR_e2 <- 0.77 # Disease Progression ## Hazard rates over time beta_e1 <- 2 # Death --> Increasing risk over time beta_e2 <- 1 # Disease Progression --> Constant risk over time ## Correlation rho <- 0.1 # Correlation between components rho_type <- 'Spearman' # Type of correlation measure copula <- 'Frank' # Copula used to get the joint distribution ## Additional parameter case <- 3 # 1: No deaths; 2: Death is the secondary event; # 3: Death is the primary event; 4: Both events are death by different causes ## ----------------------------------------------------------------------------- ARE_tte(p0_e1 = p0_e1 , p0_e2 = p0_e2, HR_e1 = HR_e1 , HR_e2 = HR_e2, beta_e1 = beta_e1 , beta_e2 = beta_e2, rho = rho , rho_type = rho_type, copula = copula , case = case, plot_print = TRUE) ## ----warning=FALSE------------------------------------------------------------ effectsize_tte(p0_e1 = p0_e1 , p0_e2 = p0_e2, HR_e1 = HR_e1 , HR_e2 = HR_e2, beta_e1 = beta_e1 , beta_e2 = beta_e2, rho = rho , rho_type = rho_type, copula = copula , case = case, plot_print = TRUE) ## ----------------------------------------------------------------------------- samplesize_tte(p0_e1 = p0_e1 , p0_e2 = p0_e2, HR_e1 = HR_e1 , HR_e2 = HR_e2, beta_e1 = beta_e1 , beta_e2 = beta_e2, rho = rho , rho_type = rho_type, copula = copula , case = case, alpha = 0.025 , power = 0.90, ss_formula = 'schoenfeld', plot_print = TRUE) ## ----warning=FALSE------------------------------------------------------------ ## Hazards' rates over time Scenario 1 beta_e1 <- 1 # Death --> CONSTANT over time beta_e2 <- 2 # Disease Progression --> INCREASE over time effectsize_tte(p0_e1 = p0_e1 , p0_e2 = p0_e2, HR_e1 = HR_e1 , HR_e2 = HR_e2, beta_e1 = beta_e1 , beta_e2 = beta_e2, rho = rho , rho_type = rho_type, copula = copula , case = case, plot_print = TRUE) ## Hazards' rates over time Scenario 2 beta_e1 <- 1 # Death --> CONSTANT over time beta_e2 <- 1 # Disease Progression --> CONSTANT over time effectsize_tte(p0_e1 = p0_e1 , p0_e2 = p0_e2, HR_e1 = HR_e1 , HR_e2 = HR_e2, beta_e1 = beta_e1 , beta_e2 = beta_e2, rho = rho , rho_type = rho_type, copula = copula , case = case, plot_print = TRUE) ## ----warning=FALSE, fig.width=6, fig.height=6--------------------------------- plot_tte(p0_e1 = p0_e1 , p0_e2 = p0_e2, HR_e1 = HR_e1 , HR_e2 = HR_e2, beta_e1 = beta_e1 , beta_e2 = beta_e2, rho = rho , rho_type = rho_type, copula = copula , case = case, summary = TRUE) ## ----------------------------------------------------------------------------- plot_tte(p0_e1 = p0_e1 , p0_e2 = p0_e2, HR_e1 = HR_e1 , HR_e2 = HR_e2, beta_e1 = beta_e1 , beta_e2 = beta_e2, rho = rho , rho_type = rho_type, copula = copula , case = case, summary = FALSE , type = 'ARE') + ggtitle('Asymptotic Relative Efficiency') + theme_bw() ## ----echo = FALSE------------------------------------------------------------- rm(list = ls())