# 3AFC with positional bias parameters
model 3AFC
{
#priors for parameters d, b1, b2
d~dnorm(0,.1)I(0,)
b1~dnorm(0,.1)
b2~dnorm(0,.1)

z[1] <- 1
z[2] <- -1
z[3] <- 0
z1[1] <- -1
z1[2] <- 0
z1[3] <- 1
z2[1] <- 0
z2[2] <- -1
z2[3] <- 1

for(i in 1:3){
  mu1[i,1] <- b1-b2+d*z[i]
  mu1[i,2] <- b2-b1-d*z[i]
  mu1[i,3] <- -b1+d*z1[i]
  mu2[i,1] <- b1-d*z1[i]
  mu2[i,2] <- b2-d*z2[i]
  mu2[i,3] <- -b2+d*z2[i]
  for(j in 1:3){
      for(k in 1:n[i,j]){
      y[i,j,k] <- 1
	  eps[i,j,k] ~ dnorm(0,1.0)
	  mn[i,j,k,1] <- mu1[i,j]
	  mn[i,j,k,2] <- mu2[i,j]
  	p[i,j,k] <- phi(mn[i,j,k,1] + eps[i,j,k])*phi(mn[i,j,k,2]+eps[i,j,k])
	  y[i,j,k] ~ dbern(p[i,j,k])
   	  }
      }
   }
}

#data
list(n=structure(.Data=c(54,5,1,0,60,0,5,3,52),.Dim=c(3,3)))

list(n=structure(.Data=c(40,12,8,6,49,4,6,5,49),.Dim=c(3,3)))