The baskwrap package supplies a unified wrapper to several basket trial
packages (basksim and baskexact) using a unified syntax.
Installation
You can install the development version of baskwrap from GitHub with:
# install.packages("pak") pak::pak("LukasDSauer/baskwrap")
Example
The baskwrap package provides a simple interface to switch between two methods for calculating basket trial characteristics, numerical integration (“exact”) and Monte Carlo simulation (“simulated”).
library(baskwrap) # INPUT PARAMETERS n <- 20 p1 <- c(0.2, 0.5, 0.5) lambda <- 0.95 epsilon <- 2 tau <- 0.5 design <- setup_fujikawa_x(k = 3, p0 = 0.2, backend = "exact") # DETAILS USING EXACT BACKEND get_details(design = design, n = n, p1 = p1, lambda = lambda, epsilon = epsilon, tau = tau) #> $Rejection_Probabilities #> [1] 0.1656753 0.9623016 0.9623016 #> #> $FWER #> [1] 0.1656753 #> #> $EWP #> [1] 0.9983541 #> #> $Mean #> [1] 0.2358052 0.4958199 0.4958199 #> #> $MSE #> [1] 0.009524536 0.009835315 0.009835315 #> #> $Lower_CL #> numeric(0) #> #> $Upper_CL #> numeric(0) #> #> $ECD #> [1] 2.758928 #> #> $p0 #> [1] 0.2 #> #> $p1 #> [1] 0.2 0.5 0.5 #> #> $backend #> [1] "exact" # DETAILS USING MC BACKEND get_details(design = set_backend(design, "sim"), n = n, p1 = p1, lambda = lambda, epsilon = epsilon, tau = tau) #> $Rejection_Probabilities #> [1] 0.146 0.967 0.958 #> #> $FWER #> [1] 0.146 #> #> $EWP #> [1] 0.999 #> #> $Mean #> [1] 0.2319132 0.4989091 0.4931409 #> #> $MSE #> [1] 0.009404904 0.009455926 0.009624520 #> #> $Lower_CL #> [1] 0.09135332 0.34169623 0.33677898 #> #> $Upper_CL #> [1] 0.3866402 0.6558876 0.6494963 #> #> $ECD #> [1] 2.779 #> #> $Rejection_Probabilities_SE #> [1] 0.011166199 0.005648982 0.006343185 #> #> $FWER_SE #> [1] 0.0111662 #> #> $EWP_SE #> [1] 0.0009994999 #> #> $ECD_SE #> [1] 0.01327913 #> #> $p0 #> [1] 0.2 #> #> $p1 #> [1] 0.2 0.5 0.5 #> #> $backend #> [1] "sim"