model_norm.txt

 model {

     #N = nobs
     for (i in 1:N) {

     # conditional treatment assignment model, v2;
     a_2[i] ~ dbern(p2c[i])
     logit(p2c[i]) <- b20 + b21*w1[i]+ b22*w2[i] + b23*L1_1[i] + b24*L2_1[i] + b25*L1_2[i] + b26*L2_2[i] + b27*a_1[i]

     # marginal treatment assignment model, v2;
     a_2m[i] ~ dbern(p2m[i])
     logit(p2m[i]) <- bm20 + bm21*a_1[i]

     # conditional treatment assignment model, v1;
     a_1[i] ~ dbern(p1c[i])
     logit(p1c[i]) <- b10 + b11*w1[i]+ b12*w2[i] + b13*L1_1[i] + b14*L2_1[i]

     # marginal treatment assignment model, v1;
     a_1m[i] ~ dbern(p1m[i])
     logit(p1m[i]) <- bm10

     }

     # Priors
     b10 ~ dnorm(0,10) 
     b11 ~ dnorm(0,5) 
     b12 ~ dnorm(0,5) 
     b13 ~ dnorm(0,5) 
     b14 ~ dnorm(0,5) 
     
     b20 ~ dnorm(0,10)
     b21 ~ dnorm(0,5)
     b22 ~ dnorm(0,5)
     b23 ~ dnorm(0,5) 
     b24 ~ dnorm(0,5)
     b25 ~ dnorm(0,5)
     b26 ~ dnorm(0,5) 
     b27 ~ dnorm(0,5) 
      
     bm10 ~ dnorm(0,10)
     bm20 ~ dnorm(0,10)
     bm21 ~ dnorm(0,5)


     }