get_evaluation.fujikawa: Evaluate a Basket Trial with Fujikawa's Design

In basksim: Simulation-Based Calculation of Basket Trial Operating Characteristics

Evaluate a Basket Trial with Fujikawa's Design

Description

Evaluate a Basket Trial with Fujikawa's Design

Usage

## S3 method for class 'fujikawa'
get_evaluation(
  design,
  n,
  r,
  lambda,
  level = 0.95,
  epsilon,
  tau,
  logbase = 2,
  ...
)

Arguments

design	An object of class fujikawa.
n	The sample sizes of the baskets. A vector must be used for varying sample sizes.
r	Vector of responses.
lambda	The posterior probability threshold.
level	Level of the credibility intervals.
epsilon	Tuning parameter that determines the amount of borrowing. See setup_fujikawa).
tau	Tuning parameter that determines how similar the baskets have to be that information is shared. See setup_fujikawa).
logbase	Tuning parameter. The base of the logarithm that is used to calculate the Jensen-Shannon divergence.
...	Further arguments.

Value

A list containing the point estimates of the basket-specific response rates and the posterior probabilities that the estimated response rates are above a specified threshold p0.

Examples

design <- setup_fujikawa(k = 3, p0 = 0.2)

# Equal sample sizes
get_evaluation(design = design, n = 20, r = c(10, 15, 5),
  lambda = 0.95, epsilon = 2, tau = 0, iter = 100)

# Unequal sample sizes
get_evaluation(design = design, n = c(15, 20, 25),
   r = c(10, 15, 17), lambda = 0.95, epsilon = 2,
   tau = 0, iter = 100)

basksim documentation built on May 12, 2026, 9:08 a.m.