RBesT (version 1.2-2)

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

See Also

pBetaBinomial, rBetaBinomial

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 {
# }