setup_exnex {basksim}

Setup EXNEX Design Object

Description

Setup EXNEX Design Object

Usage

setup_exnex(
  k,
  p0,
  basket_mean = NULL,
  basket_sd = 100,
  mu_mean = NULL,
  mu_sd = 100
)

Arguments

k

The number of baskets.

p0

A common probability under the null hypothesis.

basket_mean

Mean of the normal prior distribution of the individual thetas (NEX part). See details.

basket_sd

Standard deviation of the normal prior distribution of the individual thetas (NEX part).

mu_mean

Mean of the normal prior exchangeability distribution for the mean of the thetas (EX part). See details.

mu_sd

Standard deviation of the normal prior exchangeability distribution for the mean of the thetas (EX part).

Details

The class exnex implements the EXNEX model proposed by Neuenschwander et al. (2016). Methods for this class are mostly wrappers for functions from the package bhmbasket.

In the EXNEX model the thetas of all baskets are modeled as a mixture of individual models and a Bayesian Hierarchical Model with a fixed mixture weight w. If mu_mean and basket_mean are NULL then they are set to logit(p0). Note that Neuenschwander et al. (2016) use different prior means and standard deviations. The default values here are used for better comparison with the BHM model (see setup_bhm).

Value

An S3 object of class exnex

References

Neuenschwander, B., Wandel, S., Roychoudhury, S., & Bailey, S. (2016). Robust exchangeability designs for early phase clinical trials with multiple strata. Pharmaceutical statistics, 15(2), 123-134.

Examples

design_exnex <- setup_exnex(k = 3, p0 = 0.2)