This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Hazen, G. B. Search for Related Content PubMed PubMed Citation Articles by Hazen, G. B. Social Bookmarking                         What's this?

Stochastic Trees

A New Technique for Temporal Medical Decision Modeling

This paper introduces stochastic trees, a new modeling approach for the class of medical decision problems in which risks of mortality and morbidity may extend over time. A stochastic tree may be regarded as a continuous-time version of a Markov-cycle tree, or alternately, as a multi-state DEALE model. Optimal decisions in stochastic trees can be determined by rollback, much in the same fashion as decision trees. The author discusses how age- dependent mortality rates and declining incidence rates may be modeled using stochastic trees. Concepts are illustrated using examples from the medical literature. It is argued that stochastic trees possess important advantages over Markov-cycle trees for medical decision modeling. Key words: stochastic trees; DEALE models; decision analysis; Markov cycle trees. (Med Decis Making 1992;12:163-178)

Medical Decision Making, Vol. 12, No. 3, 163-178 (1992)
DOI: 10.1177/0272989X9201200302


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				G. B. Hazen and A. Schwartz Incorporating Extrinsic Goals Into Decision and Cost-Effectiveness Analyses Med Decis Making, September 1, 2009; 29(5): 580 - 589. [Abstract] [PDF]

				G. B. Hazen Adding Extrinsic Goals to the Quality-Adjusted Life Year Model Decision Analysis, March 1, 2007; 4(1): 3 - 16. [Abstract] [PDF]

				G. B. Hazen and M. Huang Parametric Sensitivity Analysis Using Large-Sample Approximate Bayesian Posterior Distributions Decision Analysis, December 1, 2006; 3(4): 208 - 219. [Abstract] [PDF]

				G. B. Hazen and M. Huang Large-Sample Bayesian Posterior Distributions for Probabilistic Sensitivity Analysis Med Decis Making, September 1, 2006; 26(5): 512 - 534. [Abstract] [PDF]

				N. J. Welton and A. E. Ades Estimation of Markov Chain Transition Probabilities and Rates from Fully and Partially Observed Data: Uncertainty Propagation, Evidence Synthesis, and Model Calibration Med Decis Making, November 1, 2005; 25(6): 633 - 645. [Abstract] [PDF]

				D. M. Bravata, K. M. McDonald, H. Szeto, W. M. Smith, C. Rydzak, and D. K. Owens A Conceptual Framework for Evaluating Information Technologies and Decision Support Systems for Bioterrorism Preparedness and Response Med Decis Making, March 1, 2004; 24(2): 192 - 206. [Abstract] [PDF]

				G. Hazen Preference Factoring for Stochastic Trees Management Science, March 1, 2000; 46(3): 389 - 403. [Abstract] [PDF]

				G. B. Hazen, J. M. Pellissier, and J. Sounderpandian Stochastic-Tree Models in Medical Decision Making Interfaces, July 1, 1998; 28(4): 64 - 80. [Abstract] [PDF]

				R. W. Chang, J. M. Pellissier, and G. B. Hazen A Cost-effectiveness Analysis of Total Hip Arthroplasty for Osteoarthritis of the Hip JAMA, March 20, 1996; 275(11): 858 - 865. [Abstract] [PDF]

				G. B. Hazen Factored Stochastic Trees: A Tool for solving Complex Temporal Medical Decision Models Med Decis Making, August 1, 1993; 13(3): 227 - 236. [Abstract] [PDF]