JSD: JSD (Fujikawa et al., 2020) Method for Bayesian Basket Trial

In BasketTrial: Bayesian Basket Trial Design and Analysis

JSD (Fujikawa et al., 2020) Method for Bayesian Basket Trial

Description

JSD (Fujikawa et al., 2020) Method for Bayesian Basket Trial

Usage

JSD(nDat, yDat, be.a0 = NULL, be.b0 = NULL, epsilon = 2, tau = 0.3)

Arguments

nDat	a vector of length B for the sample size in each basket.
yDat	a vector of length B for the number of responses in each basket.
be.a0	a vector of length B for beta prior parameter a0 in each basket.
be.b0	a vector of length B for beta prior parameter b0 in each basket.
epsilon	the global control parameter in the JSD model.
tau	the threshold parameter in the JSD model.

Value

It returns a list including the posterior beta parameters and similarity matrix.

References

Fujikawa, K., Teramukai, S., Yokota, I., & Daimon, T. (2020). A Bayesian basket trial design that borrows information across strata based on the similarity between the posterior distributions of the response probability. Biometrical Journal, 62(2), 330-338.

Examples

JSD(nDat = c(25, 25, 25, 25, 25), yDat = c(2,9,11,13,20))

BasketTrial documentation built on June 18, 2025, 5:08 p.m.