Post_Prob: Bayesian posterior probability, given 1 observed proportion

In IDDI-BE/PhII_Bayes: Bayesian tools for PhII clinical trial design

Description

This function calculates the Bayesian posterior probability P(Delta>Dcut|n,x) ~beta(beta_par[1]+x,beta_par[2]+n-x) with prior beta distribution beta_par

Usage

Post_Prob(n, x, beta_par, Dcut)

Arguments

n	number of patients
x	number of successes
beta_par	two shape parameters c(alpha,beta) for beta distribution
Dcut	Proportion corresponding with some hypothesis

Value

Bayesian posterior probability

Examples

## Not run: 
Post_Prob.f(n=40,x=16,beta_par=c(0.6,0.4),Dcut=0.6) # Example Lee 2008, p97, Table 1 
(first line of Panel B: Y=0)

## End(Not run)

IDDI-BE/PhII_Bayes documentation built on May 19, 2021, 3:04 p.m.