17.9 Chapter summary

• \(Y_{ij}|\beta_j, \sigma_y \sim N(\mu_{ij}, \sigma²_y)\) : regression model within group \(j\)

• \(\beta_j|\beta, \sigma \sim N(\beta, \sigma^2)\) : variability in regression parameters between group

• \(\beta, \sigma_y, \sigma, ... \sim ...\) priors models on global parameters

Either we go with a random intercepts models or we use a random intercepts and slopes model.