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Recursive Utility for Stochastic Trees

Author

Listed:
  • Gordon B. Hazen

    (Northwestern University, Evanston, Illinois)

  • James M. Pellissier

    (Loyola University, Chicago, Illinois)

Abstract

Stochastic trees are semi-Markov processes represented using tree diagrams. Such trees have been found useful for prescriptive modeling of temporal medical treatment choice. We consider utility functions over stochastic trees which permit recursive evaluation in a graphically intuitive manner analogous to decision tree rollback. Such rollback is computationally intractable unless a low-dimensional preference summary exists. We present the most general classes of utility functions having specific tractable preference summaries. We examine three preference summaries— memoryless, Markovian , and semi-Markovian —which promise both computational feasibility and convenience in assessment. Their use is illustrated by application to a previous medical decision analysis of whether to perform carotid endarterectomy.

Suggested Citation

  • Gordon B. Hazen & James M. Pellissier, 1996. "Recursive Utility for Stochastic Trees," Operations Research, INFORMS, vol. 44(5), pages 788-809, October.
    • Handle: RePEc:inm:oropre:v:44:y:1996:i:5:p:788-809
    DOI: 10.1287/opre.44.5.788
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    Citations

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    Cited by:

    1. Gordon Hazen, 2000. "Preference Factoring for Stochastic Trees," Management Science, INFORMS, vol. 46(3), pages 389-403, March.
    2. Gordon Hazen, 2004. "Multiattribute Structure for QALYs," Decision Analysis, INFORMS, vol. 1(4), pages 205-216, December.
    3. A. E. Ades & G. Lu & K. Claxton, 2004. "Expected Value of Sample Information Calculations in Medical Decision Modeling," Medical Decision Making, , vol. 24(2), pages 207-227, March.
    4. Nicky J. Welton & A. E. Ades, 2005. "Estimation of Markov Chain Transition Probabilities and Rates from Fully and Partially Observed Data: Uncertainty Propagation, Evidence Synthesis, and Model Calibration," Medical Decision Making, , vol. 25(6), pages 633-645, November.
    5. Ali E. Abbas, 2011. "The Multiattribute Utility Tree," Decision Analysis, INFORMS, vol. 8(3), pages 180-205, September.
    6. B. P. S. Murthi & Sumit Sarkar, 2003. "The Role of the Mangement Sciences in Research on Personalization," Review of Marketing Science Working Papers 2-2-1025, Berkeley Electronic Press.
    7. Alexander Begun & Andrea Icks & Regina Waldeyer & Sandra Landwehr & Michael Koch & Guido Giani, 2013. "Identification of a Multistate Continuous-Time Nonhomogeneous Markov Chain Model for Patients with Decreased Renal Function," Medical Decision Making, , vol. 33(2), pages 298-306, February.

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