  We present an overview of the decision-theoretic framework of statistical
causality, which is well-suited for formulating and solving problems of
determining the effects of applied causes. The approach is described in detail,
and is related to and contrasted with other current formulations, such as
structural equation models and potential responses. Topics and applications
covered include confounding, the effect of treatment on the treated,
instrumental variables, and dynamic treatment strategies.
