sim_basket: Simulate a basket trial under several study design choices...

In massimoventrucci/INLAbhmbasket: Simulate the operating characteristics of a basket trial via Bayesian Hierarchical Modelling (BHM) using INLA

Simulate a basket trial under several study design choices and priors on the arm-level variance

Description

MANUAL IN PROGRESS; ...

Usage

sim_basket(nsim, m, N, p_true, p_null, p_target, ia1_fraction = 0.4, step = 0.5, futility_threshold = 0.05, efficacy_threshold = 0.9, prior, parameters)

Arguments

nsim	number of simulated trials
m	number of arms
N	max number of patients enrolled per arm (same for each arm)
p_true	a vector of length \textttm with response rate for generating the data in each arm
p_null	the null hypothesis uninteresting threshold (efficacy rate under H0)
p_target	the alternative hypothesis target threshold (efficacy rate under H1)
ia1_fraction	a fraction of N at which the 1st interim analysis (IA) takes place; default 0.4
step	define subsequent IAs' timing as an increment of the patients enrolled at the 1st IA; default 0.5
futility_threshold	response rate at which the arm can be closed based on futility; default 0.05
efficacy_threshold	response rate at which the arm can be closed based on efficacy; default 0.9
prior	prior distribution for the arm-level variance, choices are: \beginitemize \item Gamma(a, b) on the precision; \item half-t(gamma, ni) on the standard deviation (\texttthalf-t); \item uniform (a, b) on the standard deviation; \item PC(sd_x) prior (\textttPC); \item EPC (please use the EPC_sd function to compute the desired sd_x value, TODO...); \enditemize
parameters	parameters of the prior distrinution on the arm-level variance

Details

bla

Value

bla

Note

bla

Author(s)

bla

References

bla

See Also

bla

massimoventrucci/INLAbhmbasket documentation built on July 5, 2022, midnight