RBesT (version 1.3-7)

dBetaBinomial: Beta-Binomial Probabilities

Description

Beta-Binomial Probabilities

Usage

dBetaBinomial(r, n, a, b, log = FALSE)

Arguments

r, n

number of successes (responders) out of n

a, b

parameters of the Beta distribution for response probability

Details

r,n,a,b can be scalar or vectors. If vectors are used, they must be of the same length

Examples

# NOT RUN {
# }
# NOT RUN {
# Ex1: Predictive distribution for uniform p
Ex1 =  dBetaBinomial( r=0:9,n=9,a=1,b=1)
Ex1

# Ex2: Predictive distribution at interim: n1=20, n=50
# Interim data: 4/20
# Probability to have 6 or more responders in 50 patients?
# That is: predictive probability >=2 in remaining 30?

# 1) Assume a weakly-informative Beta(a,1) prior with median 0.1 at trial start:
a = log(0.5)/log(0.1); b=1
p = dBetaBinomial(r=0:1,n=30,a=a+4,b=b+16)
1-sum(p)

# 2) Assume a uniform prior at trial start:
p = dBetaBinomial(r=0:1,n=30,a=1+4,b=1+16)
1-sum(p)
# }
# NOT RUN {
# }