calibrate: calibrate

In brada: Bayesian Response-Adaptive Design Analysis

calibrate

Description

Calibrates a brada object to achieve specified false-positive and false-negative rates.

Usage

calibrate(brada_object, nsim = 100, cores = 2, seq, 
alpha=NULL, beta=NULL, calibration = "nu")

Arguments

brada_object	An object of class brada
nsim	Number of Monte Carlo iterations
cores	Number of cores used for computation
seq	Sequence of values for the evidence threshold nu, or sequence of the futility threshold theta_L, depending on which value is passed to the function in the calibration argument. For example, seq=seq(0,1,0.1) in combination with calibration="nu" and alpha=0.1 implies that the function tries to calibrate the false-positive rate to decrease below alpha=0.1 by iteratively increasing nu from zero to one in steps of size 0.1.
alpha	Upper bound for false-positive rate. Note that it is only possible to specify either alpha or beta. When alpha is passed as an argument, calibration should take the value "nu", while when beta is passed as an argument, calibration should take the value "theta_L".
beta	Upper bound for false-negative rate
calibration	String which specifies which parameter to calibrate. Can take the values "nu" or "theta_L".

Value

Prints the output to the console and returns the false-positive rate or false-negative rate of the calibrated design, depending on which value the calibration argument takes.

Author(s)

Riko Kelter

brada documentation built on Feb. 16, 2023, 6:53 p.m.