The article discusses using Bayesian methods to combine results from different experiments. The researchers focus on estimating normal means by grouping parameters and using a hierarchical approach. They use Gibbs sampling to implement these Bayesian procedures. The key idea is that components within a subgroup are interchangeable, but different subgroups are not. The researchers show how this method works with numerical examples.