doseresNMA antidep/drnma.model.standardRE.R

In htx-r/doseresNMA:

# RE delta's
drnma.standardRE <- function(){
  for(i in 1:ns){ # loop through ns trials
    w[i,1] <-0
    delta[i,1] <- 0
    u[i] ~ dnorm(0,0.001) # baseline effect

    for (k in 1:na[i]){ # loop through na arms within a study
      r[i,k] ~ dbin(p[i,k], n[i,k])
      logit(p[i,k]) <- theta[i,k]
      theta[i,k] <- u[i] + delta[i,k]

      # arm deviance
      rhat[i,k] <- p[i,k] * n[i,k]
      resdev[i,k] <- 2 * (r[i,k] * (log(r[i,k]) - log(rhat[i,k])) + (n[i,k] - r[i,k]) * (log(n[i,k] - r[i,k]) - log(n[i,k] - rhat[i,k])))

    }

    # study deviance
    resstudydev[i] <- sum(resdev[i, 1:na[i]])

    for(k in 2:na[i]){ # treatment effects
      #- RE delta's
      delta[i,k]~dnorm(md[i,k], prec[i,k])
      DE[i,k] <- ((beta1[t[i,k]] * dose1[i,k])+(beta2[t[i,k]] * dose2[i,k])) - ((beta1[t[i,1]] * dose1[i,1]) + (beta2[t[i,1]] * dose2[i,1]))

      md[i,k] <- DE[i,k] + sw[i,k]

      prec[i,k] <- prec.d *2*(k-1)/k

      w[i,k] <- delta[i,k] - DE[i,k]

      sw[i,k] <-sum(w[i,1:(k-1)])/(k-1)
         }
  }

  # PRIORS
  # to delta's RE model
  tau.d~dunif(0,5)      # delta's SE prior
  prec.d<-1/pow(tau.d,2) #  delta's precision

  # to beta's
  beta2[ref.index] <- 0
  beta1[ref.index] <- 0
  for (k in c(1:(ref.index - 1), (ref.index + 1):ndrugs)){
    beta1[k]~dnorm(0, 0.001)
    beta2[k]~dnorm(0, 0.001)
  }

  # overall deviance
  totresdev <- sum(resstudydev[])

  #** drug absoulte effect

  # baseline effect
  for (m in 1:ns){
    rr[m,1] ~ dbinom(p0[m],nn[m,1])
    logit(p0[m]) <- OO[m]
    OO[m] ~ dnorm(Z, prec.z)
  }
  # baseline priors
  Z ~ dnorm(0, 0.001)
  prec.z <- pow(sigma.z,-2)
  sigma.z ~ dunif(0,10)
  p.placebo <- exp(Z)/(1+exp(Z))
  # combine baseline with OR -> drug absolute effect
  for (k in c(1:(ref.index-1),(ref.index+1):ndrugs)){
    for( j in 1:nd.new){
      OR[j,k] <- exp(beta1[k]*new.dose[k,j]+  beta2[k]*f.new.dose[k,j])
      odds.drug[j,k] <- OR[j,k]*exp(Z)
      p.drug[j,k] <- odds.drug[j,k]/(1+odds.drug[j,k])
    }
  }
}