model
		{
			for (i in 1 : Dogs) {
				xa[i, 1] <- 0; xs[i, 1] <- 0 p[i, 1] <- 0 
				for (j in 2 : Trials) {
					xa[i, j] <- sum(Y[i, 1 : j - 1])
					xs[i, j] <- j - 1 - xa[i, j]
					log(p[i, j]) <- alpha * xa[i, j] + beta * xs[i, j]
					y[i, j] <- 1 - Y[i, j]
					y[i, j] ~ dbern(p[i, j])					
				}
			} 
			alpha ~ dnorm(0, 0.00001)I(, -0.00001)
			beta ~ dnorm(0, 0.00001)I(, -0.00001)
			A <- exp(alpha)
			B <- exp(beta)
		}