basket_test {baskexact} | R Documentation |
basket_test
evaluates the results of a basket trial and calculates
the posterior distributions with and without borrowing.
basket_test(design, n, r, lambda, epsilon, tau, logbase = 2, prune, ...)
## S4 method for signature 'OneStageBasket'
basket_test(design, n, r, lambda, epsilon, tau, logbase = 2, prune, ...)
design |
An object of class |
n |
The sample size per basket. |
r |
The vector of observed responses. |
lambda |
The posterior probability threshold. See details for more information. |
epsilon |
A tuning parameter that determines the amount of borrowing. See details for more information. |
tau |
A tuning parameter that determines how similar the baskets have to be that borrowing occurs. See details for more information. |
logbase |
A tuning parameter that determines which logarithm base is used to compute the Jensen-Shannon divergence. See details for more information. |
prune |
Whether baskets with a number of responses below the critical pooled value should be pruned before the final analysis. |
... |
Further arguments. |
A list, including matrices of the weights that are used for borrowing, posterior distribution parameters for all baskets without and with borrowing, as well as the posterior probabilities for all baskets without and with borrowing.
OneStageBasket
: Testing for a single-stage basket design.
design <- setupOneStageBasket(k = 3, shape1 = 1, shape2 = 1, theta0 = 0.2)
basket_test(design = design, n = 24, r = c(5, 9, 10), lambda = 0.99,
epsilon = 1, tau = 0, logbase = 2, prune = FALSE)