model{
  ### Logistic regression
  for (i in 1:n){
		returned[i] ~ dbern(p[i])
		logit(p[i]) <- beta0 + in.mod.sex*beta1*S[i] + in.mod.len*beta2*L[i] + in.mod.int*beta12*SL[i]
	}
  
  ### Priors
  beta0 ~ dt(0,0.04,3)
  beta1 ~ dt(0,0.25,3)
  beta2 ~ dt(0,0.25,3)
  beta12 ~ dt(0,0.25,3)
  
  ### Model indicator
  mod ~ dcat(p.model[1:5]) 
  
  ### Determining whether terms are in the model
  mod4 <- (mod==4)
  mod5 <- (mod==5)
	in.mod.sex <- (mod==2) + mod4 + mod5
	in.mod.len <- (mod==3) + mod4 + mod5
	in.mod.int <- mod5

  ### Predicting the observation
  logit(pred.prob) <- beta0 + in.mod.sex*beta1*sexpred + in.mod.len*beta2*lenpred + in.mod.int*beta12*sexlenpred
}