model {
# tau ~ dgamma(20, 2000)
tau ~ dgamma(10, 1000) # discounted by 2
# theta ~ dnorm(5, 0.25)
theta ~ dnorm(4, 0.125)I(0,) # 4 added to var and shifted
# by -1, constrained to be >0
sigma <- 1/sqrt(tau)
n <- 2*pow((1.28 + 1.96)*sigma/theta, 2) # n for 90% power
power <- phi(sqrt(84/2)*theta/sigma - 1.96) # power for n = 84
p70 70%)
}

node mean sd MC error 2.5% median 97.5% start sample
n 4.542E+6 4.263E+8 4.26E+6 20.96 125.6 14270.0 1 10000
p70 0.5398 0.4984 0.005085 0.0 1.0 1.0 1 10000
power 0.6536 0.3315 0.003406 0.04353 0.7549 1.0 1 10000