The common normal distribution for the child-specific random intercepts produces partial pooling. Children with little information borrow strength from the common population, while well-observed children retain more of their individual estimate. For fixed slopes and hyperparameters, let average the three responses after subtracting their slope terms. Multiplying the normal likelihood by the normal intercept prior distribution gives
with conditional variance . Thus small between-child variation produces stronger shrinkage towards . The common mean and variation are themselves learned from all children in this hierarchical Bayesian model.

Articles by others on the same topic (0)

There are currently no matching articles.