get_results.jsdglobal {basksim}

Get Results for Simulation of a Basket Trial with the Power Prior Design Based on Global JSD Weights

Description

Get Results for Simulation of a Basket Trial with the Power Prior Design Based on Global JSD Weights

Usage

## S3 method for class 'jsdglobal'
get_results(
  design,
  n,
  p1 = NULL,
  lambda,
  eps_pair,
  tau = 0,
  eps_all,
  logbase = 2,
  iter = 1000,
  data = NULL,
  ...
)

Arguments

design

An object of class jsdgen.

n

The sample size per basket.

p1

Probabilities used for the simulation. If NULL then all probabilities are set to p0.

lambda

The posterior probability threshold.

eps_pair

Tuning parameter that determines the amount of borrowing based on pairwise similarity.

tau

Tuning parameter that determines how similar the baskets have to be that information is shared.

eps_all

Tuning parameter that determines the amount of borrowing based on overall heterogeneity.

logbase

Tuning parameter. The base of the logarithm that is used to calculate the Jensen-Shannon divergence.

iter

The number of iterations in the simulation. Is ignored if data is specified.

data

A data matrix with k column with the number of responses for each basket. Has to be generated with get_data. If data is used, then iter is ignored.

...

Further arguments.

Value

A matrix of results with iter rows. A 0 means, that the null hypothesis that the response probability exceeds p0 was not rejected, a 1 means, that the null hypothesis was rejected.

Examples

design <- setup_jsdglobal(k = 3, p0 = 0.2)
get_results(design = design, n = 20, p1 = c(0.2, 0.5, 0.5), lambda = 0.95,
  eps_pair = 2, eps_all = 2, iter = 100)