Cluster Allocation Design Networks*
Ana Maria Madrigal · 2007
Abstract Policy makers usually define a strategy that involves policy assignment and recording mechanisms. Causal inference is sensitive to the specification of these mechanisms. Influence diagrams have been used for causal reasoning within a Bayesian decision-theoretic framework (Dawid, 2002). Design Networks (DNs) expand this framework by including experimental design decision nodes. DNs provide semantics to discuss how a design decision strategy might assist the identification of intervention causal effects. The DN framework is extended to Cluster Allocation. Cases of ‘pure’ cluster (all individuals in a cluster receiving the same intervention) and ‘non-pure’ cluster (only a subset receiving the policy) are discussed in terms of causal effects.