model
{
    for (i in 1:n) {

                                    #  Linear regression on logit
  logit(p[i]) <- alpha + b.sex*sex[i] + b.age*age[i]

                                    #  Likelihood function for each data point
    frac[i]   ~ dbern(p[i])
    }
    alpha     ~ dnorm(0.0,1.0E-4)   #  Prior for intercept
    b.sex     ~ dnorm(0.0,1.0E-4)   #  Prior for slope of sex
    b.age     ~ dnorm(0.0,1.0E-4)   #  Prior for slope of age
}

# Data

list(sex=c(1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0,
1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0,
0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1,
0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1,
1, 1, 0, 1, 1, 1, 1, 1),
age= c(69, 57, 61, 60, 69, 74, 63, 68, 64, 53, 60, 58, 79, 56, 53, 74,
56, 76, 72, 56, 66, 52, 77, 70, 69, 76, 72, 53, 69, 59, 73, 77, 55, 77,
68, 62, 56, 68, 70, 60, 65, 55, 64, 75, 60, 67, 61, 69, 75, 68, 72, 71,
54, 52, 54, 50, 75, 59, 65, 60, 60, 57, 51, 51, 63, 57, 80, 52, 65, 72,
80, 73, 76, 79, 66, 51, 76, 75, 66, 75, 78, 70, 67, 51, 70, 71, 71, 74,
74, 60, 58, 55, 61, 65, 52, 68, 75, 52, 53, 70),
frac=c(1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0,
1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1,
0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1,
1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1,
0, 0, 1, 0, 0, 1),
n=100)

# Inits

list(alpha=0, b.sex=1, b.age=1)


# Results

| node  | mean   | sd     | MC error | 2.5%    | median | 97.5%  | start |sample

| alpha | -22.55 | 5.013  | 0.6062   | -34.33  | -21.64 | -14.29 | 1001  |  4000
| b.age | 0.3559 | 0.07771| 0.009395 | 0.227   | 0.3418 | 0.5338 | 1001  |  4000
| b.sex | 1.405  | 0.7719 | 0.05094  | -0.0387 | 1.374  | 3.031  | 1001  |  4000
| p[1]  | 0.9575 | 0.03153| 0.002943 | 0.879   | 0.9647 | 0.9952 | 1001  |  4000
| p[2]  | 0.307  | 0.09828| 0.004853 | 0.13    | 0.3012 | 0.5082 | 1001  |  4000
| p[3]  | 0.6308 | 0.1041 | 0.003344 | 0.4166  | 0.6356 | 0.8178 | 1001  |  4000
| p[4]  | 0.2477 | 0.103  | 0.007281 | 0.07738 | 0.2379 | 0.4728 | 1001  |  4000
 (etc...)