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Master protocols aim to study a range of multiple related therapies, diseases or disease subtypes within a single framework. In particular, in basket trials the objective is to explore the effectiveness of a single treatment in multiple similar populations. In analyzing these trials, it is advantageous to leverage the relationship between the groups in order to reduce the overall patient burden for all the groups involved in the study. We can accomplish this by using methods such as Bayesian hierarchical models which assume a specific relationship structure between the groups. In this presentation I will discuss the theory underlying Bayesian hierarchical models in this context, discuss some important factors that influence prior selection and discuss a recent example applied used in trial with pediatric patients with two different types of arthritis.