getPriorParameters: getPriorParameters

In bhmbasket: Bayesian Hierarchical Models for Basket Trials

getPriorParameters

Description

This function provides default prior parameters for the analysis methods that can be used in performAnalyses.

Usage

getPriorParameters(
  method_names,
  target_rates,
  n_worth = 1,
  tau_scale = 1,
  w_j = 0.5
)

Arguments

method_names	A vector of strings for the names of the methods to be used. Available methods: c("berry", "exnex", "exnex_adj", "pooled", "stratified")
target_rates	A vector of numerics in (0, 1) for the target rate of each cohort
n_worth	An integer for the number of subjects the variability of the prior should reflect response rate scale, Default: 1
tau_scale	A numeric for the scale parameter of the Half-normal distribution of τ in the methods "berry", "exnex", and "exnex_adj", Default: 1
w_j	A numeric in (0, 1) for the weight of the Ex component in the methods "exnex" and "exnex_adj", Default: 0.5

Details

Regarding the default prior parameters for "berry", "exnex", and "exnex_adj":

• "berry": The mean of μ is set to 0. Its variance is calculated as proposed in "Robust exchangeability designs for early phase clinical trials with multiple strata" (Neuenschwander et al. (2016)) with regard to n_worth. The scale parameter of τ is set to tau_scale.

• "exnex": The weight of the Ex component is set to w_j. For the Ex component: The target rate that results in the greatest variance is determined. The mean of μ is set to that target rate. The variance of μ is calculated as proposed in "Robust exchangeability designs for early phase clinical trials with multiple strata" (Neuenschwander et al. (2016)) with regard to n_worth. The scale parameter of τ is set to tau_scale. For the Nex components: The means of μ_j are set to the respective target rates. The variances of τ_j are calculated as proposed in "Robust exchangeability designs for early phase clinical trials with multiple strata" (Neuenschwander et al. (2016)) with regard to n_worth, see also getMuVar.

• "exnex_adj": The weight of the Ex component is set to w_j. For the Ex component: The target rate that results in the greatest variance is determined. The mean of μ is set to 0. The variance of μ is calculated as proposed in "Robust exchangeability designs for early phase clinical trials with multiple strata" (Neuenschwander et al. (2016)) with regard to n_worth, see also getMuVar. The scale parameter of τ is set to tau_scale. For the Nex components: The means of μ_j are set to the 0. The variances of τ_j are calculated as proposed in "Robust exchangeability designs for early phase clinical trials with multiple strata" (Neuenschwander et al. (2016)) with regard to n_worth, see also getMuVar.

• "pooled": The target rate that results in the greatest variance is determined. The scale parameter α is set to that target rate times n_worth. The scale parameter β is set to 1 - that target rate times n_worth.

• "stratified": The scale parameters α_j are set to target_rates * n_worth. The scale parameters β_j are set to (1 - target_rates) * n_worth.

Value

A list with prior parameters of class prior_parameters_list

Author(s)

Stephan Wojciekowski

References

Berry, Scott M., et al. "Bayesian hierarchical modeling of patient subpopulations: efficient designs of phase II oncology clinical trials." Clinical Trials 10.5 (2013): 720-734.

Neuenschwander, Beat, et al. "Robust exchangeability designs for early phase clinical trials with multiple strata." Pharmaceutical statistics 15.2 (2016): 123-134.

See Also

performAnalyses setPriorParametersBerry setPriorParametersExNex setPriorParametersExNexAdj setPriorParametersPooled setPriorParametersStratified combinePriorParameters getMuVar

Examples

prior_parameters_list <- getPriorParameters(
  method_names = c("berry", "exnex", "exnex_adj", "pooled", "stratified"),
  target_rates = c(0.1, 0.2, 0.3))

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