model {
for(i in 1:N){
logit(mu_M[i]) <- alpha*x[i]
M[i] ~ dbern(mu_M[i])
mu_y[i]<- c*x[i]+beta*M[i]
y[i] ~ dnorm(mu_y[i],prec2)

logit(mu_M1[i]) <- alpha*(x[i]+deltax)
M1[i] ~ dbern(mu_M1[i])

mu_y1[i]<- c*(x[i]+deltax)+beta*M[i]

mu_y2[i]<- c*x[i]
mu_y3[i]<- c*x[i]+beta

ie[i]<-(mu_M1[i]-mu_M[i])/deltax*(mu_y3[i]-mu_y2[i])/deltam
de[i]<-(mu_y1[i]-mu_y[i])/deltax
te[i]<-ie[i]+de[i]
}

alpha ~ dnorm(0.0,0.01)
beta ~ dnorm(0.0,0.01)  
c ~ dnorm(0.0,0.001) 
var2 ~ dgamma(1,0.1)
prec2 <-1/var2
}