Abstract
The stochastic tree is a recently introduced generalization of the decision tree which allows the explicit depiction of temporal uncertainty while still employing the familiar rollback procedure for decision trees. We offer an introduction to stochastic-tree modeling and techniques involved in their application to medical-treatment decisions. We also describe an application of these tools to the analysis of the decision to undergo a total hip replacement from the perspectives of an individual patient (via utility analysis) and of society (via cost-effectiveness analysis).
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