setPriorParametersExNexAdj: setPriorParametersExNexAdj

In bhmbasket: Bayesian Hierarchical Models for Basket Trials

setPriorParametersExNexAdj

Description

This function sets prior parameters for the analysis method "exnex_adj" for use in performAnalyses.

Usage

setPriorParametersExNexAdj(mu_mean, mu_sd, tau_scale, mu_j, tau_j, w_j)

Arguments

mu_mean	A numeric for the mean of μ
mu_sd	A positive numeric for the standard deviation of μ
tau_scale	A positive numeric for the scale parameter of τ
mu_j	A vector of numerics for the means μ_j
tau_j	A vector of positive numerics for the standard deviations τ_j
w_j	A numeric in (0, 1) for the weight of the Ex component

Details

This function sets the prior parameters for the method ExNex Adjusted, which combines the approach proposed by Neuenschwander et al. (2016) and the approach proposed by Berry et al. (2013).

Value

A list with prior parameters of class prior_parameters_list

Author(s)

Stephan Wojciekowski

See Also

performAnalyses getPriorParameters combinePriorParameters setPriorParametersBerry setPriorParametersExNex setPriorParametersPooled setPriorParametersStratified getMuVar

Examples

 prior_parameters_exnex_adj <- setPriorParametersExNexAdj(0, 1, 2, c(4, 5), c(6, 7), 0.8)

bhmbasket documentation built on March 18, 2022, 7:46 p.m.