trial level sampling

dpp-poc.R

X <- rnorm(n, 1)
Y <- -.5 + 1.5 * X + rnorm(n, sd = .5)
enns <- sample(ceiling(runif(n, 200, 2000)))

samp.indi.data <- function(i) {
  
  Z <- rbinom(enns[i], 1, .5)
  mu.S <- 2.5 + X[i] * Z
  lambda.T <- -1 + Y[i] * Z
  
  S <- rnorm(enns[i], mean = mu.S)
  T <- rpois(enns[i], exp(lambda.T))
  data.frame(Z, S, T)
  
  
}

library(arm)

s1 <- bayesglm(S ~ Z, data = test)
zpost <- sim(s1, n.sims = 1000)@coef[, 2]

indi.datasets <- lapply(1:n, samp.indi.data)