alphaspend: Function that calculates the upper boundaries for efficacy

In seqmon: Group Sequential Design Class for Clinical Trials

Description

Calculates the upper boundaries for efficacy at each look time

Usage

alphaspend(levels, t, int = rep(500, length(t)), tol = 0.005)

Arguments

levels	The cumulative alpha spending at each look time
t	Normalized look times
int	The number of intervals the solution space is partitioned into
tol	Tolerance of the solution using uniroot

Value

numeric

Examples

f<- function(t) 0.025*t^4
t<-c(0.33,0.67,1)
cum_probs<-f(t)
alphaspend(levels=cum_probs,t,int=rep(500, length(t)),tol=0.005)

seqmon documentation built on Sept. 5, 2020, 1:06 a.m.