drugdevelopR (version 1.0.2)

PsProg_binary: Probability of a successful program for multiarm programs with binary distributed outcomes

Description

Given we get the "go"-decision in phase II, this functions now calculates the probability that the results of the confirmatory trial (phase III) are significant, i.e. we have a statistically relevant positive effect of the treatment.

Usage

PsProg_binary(
  RRgo,
  n2,
  alpha,
  beta,
  p0,
  p11,
  p12,
  step1,
  step2,
  strategy,
  case
)

Value

The function PsProg_binary() returns the probability of a successful program

Arguments

RRgo

threshold value for the go/no-go decision rule

n2

total sample size for phase II; must be divisible by three

alpha

significance level

beta

1-beta power for calculation of sample size for phase III

p0

assumed true rate of control group

p11

assumed true rate of treatment group

p12

assumed true rate of treatment group

step1

lower boundary for effect size

step2

upper boundary for effect size

strategy

choose Strategy: 1 ("only best promising"), 2 ("all promising") or 3 (both)

case

different cases: 1 ("nogo"), 21 (treatment 1 is promising, treatment 2 is not), 22 (treatment 2 is promising, treatment 1 is not), 31 (both treatments are promising, treatment 1 is better), 32 (both treatments are promising, treatment 2 is better)

Examples

res <- PsProg_binary(RRgo = 0.8 ,n2 = 50 ,alpha = 0.05, beta = 0.1,
                            p0 = 0.6, p11 =  0.3, p12 = 0.5, step1 = 1, step2 = 0.95,
                            strategy = 3, case = 31)