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 <- step(power - 0.7) # Pr(power > 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

[example-5_3_2-power-continued0][example-5_3_2-power-continued1][example-5_3_2-power-continued2]