GSED (version 2.6)

boundaries_sim: Lower and upper boundaries for GSED

Description

boundaries_sim is used to estimate lower and upper boundaries for GSED based on simulations of trials.

Usage

boundaries_sim(K_stages, N_subsets, f, ratio_Delta_star_d1, ordering, 
increasing_theta=FALSE, seed=42, n_trials, alpha_spending, 
one_minus_alpha_spending, updateProgress=NULL)

Value

A list is returned, consisting of two vectors containing the lower and upper boundaries:

l

Vector of lower boundaries at each stage.

u

Vector of upper boundaries at each stage.

Arguments

K_stages

Integer indicating the number of stages in the design.

N_subsets

Integer representing the number of possible subgroups.

f

Vector containing the prevalence rates of each subgroup. Must be of length N_subsets.

ratio_Delta_star_d1

Vector containing the ratio between the (observed Fisher) information increments at each stage >1 with the (observed Fisher) information at stage 1. Must be of length K_stages-1.

ordering

Boolean indicating if the subgroups (theta) are ordered.

increasing_theta

Boolean indicating if greater values of theta parameters represent better treatment effects. The default value is set at FALSE.

seed

Interger representing the seed. The default value is set at 42.

n_trials

Integer indicating the number of trials to simulate.

alpha_spending

Vector containing the values of the alpha-spending function at each time of the analysis (including 0 at time 0 and alpha at time 1). Must be of length K_stages+1.

one_minus_alpha_spending

Vector containing the values of the 1-alpha-spending function at each time of the analysis (including 0 at time 0 and 1-alpha at time 1). Must be of length K_stages+1.

updateProgress

(for Rshiny application)

Author

Marie-Karelle Riviere-Jourdan

References

Baldur P. Magnusson and Bruce W. Turnbull. Group sequential enrichment design incorporating subgroup selection. Statistics in Medicine, 2013. <doi:10.1002/sim.5738>

Examples

#For testing purpose only, larger number of simulations required (see in comments below)
boundaries_sim(K_stages=2, N_subsets=3, f=c(0.6,0.2,0.2), ratio_Delta_star_d1=c(1), 
ordering=FALSE, seed=42, n_trials=3, alpha_spending=c(0,0.0125,0.025), 
one_minus_alpha_spending=c(0,0.4875,0.975))

#boundaries_sim(K_stages=2, N_subsets=3, f=c(0.6,0.2,0.2), ratio_Delta_star_d1=c(1), 
#ordering=FALSE, seed=42, n_trials=10000000, alpha_spending=c(0,0.0125,0.025), 
#one_minus_alpha_spending=c(0,0.4875,0.975))