model{
    for (i in 1:N){
# Likelihood
      Y[i]~dbern(p[i])
      logit(p[i])<- (1/(gamma - Xmin))*(gamma*logit(rho0) - Xmin*logit(theta)+(logit(theta)-logit(rho0))*X[i])
    }  #  end of for loop
# Priors
    gamma ~ dunif(Xmin, Xmax)
    rho0 ~ dunif(0,theta)
  }  #  end of BUGS code

# Data (1st patient 140, no tox):
list(Y=c(0), X=c(140), Xmin=140, Xmax =425, theta=0.333, N=1)

# Data (1st patient 140, no tox; 2nd patient 210, no tox):
list(Y=c(0,0), X=c(140,210), Xmin=140, Xmax=425, theta=0.333, N=2)	
	
# Data (1st patient 140, no tox; 2nd patient 210, tox):
list(Y=c(0,1), X=c(140,210), Xmin=140, Xmax=425, theta=0.333, N=2)	
	
# Data (1st patient 140, no tox; 2nd patient 210, no tox;
#   3rd patient 300, no response yet):
list(Y=c(0,0,NA),X=c(140,210,300),Xmin=140,Xmax=425,theta=0.333,N=3)	
	
#Inits:
  list(rho0=0.05, gamma=160)