bayes_pred_go_nogo: Predicative probabilities and decision tables

In zhuob/R4ClinicalTrial: R tools for clinical trials

Predicative probabilities and decision tables

Description

Predicative probabilities and decision tables

Usage

bayes_pred_go_nogo(
  nmax = 40,
  nmin = 1,
  p0 = 0.3,
  p1 = 0.5,
  thetats = 0.8,
  thetatf = 0.1,
  thetau = 0.95,
  thetal1 = 0.95,
  a = 1,
  b = 1
)

Arguments

nmax	max sample size
nmin	minimum sample size for the first interim
p0	lower reference value of response rate
p1	target value of response rate
thetats	posterior probability for Final Go s.t. Prob(p > p0) > thetats
thetatf	posterior probability for final NoGo Prob(p > p0) <= thetatf
thetau	Predictive probability for Go, i.e., PredP(Go) > thetau
thetal1	Predictive probability for NoGo PredP(NoGo) > thetal1
a, b	priors for beta distribution

Value

a decision table

Examples

go_nogo <- bayes_pred_go_nogo(nmax = 40, nmin = 1, p0 = 0.3, p1 = 0.5,
thetats = 0.8, thetatf = 0.1, thetau = 0.95, thetal1 = 0.95, a = 1, b = 1)

zhuob/R4ClinicalTrial documentation built on Feb. 4, 2025, 1:15 a.m.