Gordon Hazen is professor of Industrial Engineering and Management Sciences at Northwestern University. His research interests include decision analysis methodology, utility and preference theory, medical decision analysis, cost-effectiveness analysis of medical treatment decisions. He has published in leading journals including Management Science, Operations Research, The Journal of the Operational Research Society, Medical Decision Making, The Journal of the American Medical Association, The Journal of Risk and Uncertainty. He has served as Area Editor for decision analysis at Operations Research, and is a member of the editorial board of the INFORMS journal Decision Analysis.
GB Hazen and CA Magni. Average internal rate of return for risky projects (2021). The Engineering Economist, 66(2), 90-120.
E Borgonovo, GB. Hazen, Victor Richmond R. Jose, E Plischke (2021). Probabilistic sensitivity measures as information value. European Journal of Operational Research 289 (2021), 595-610.
G.B. Hazen, "Sensitivity Analysis via Information Density", Decision Analysis Today 33 (2014), 1 (May), 24-29.
G.B. Hazen, Probability: An Introduction with Applications, 602 pages.
G.B. Hazen and Zhe Li, "Cohort Decomposition for Markov Cost-Effectiveness Models", Med Decis Making 31 (2011) 1 (January/February) 19-34.
G.B. Hazen (2009), "An Extension of the Internal Rate of Return to Stochastic Cash Flows", Management Science 55 (6) 1030-1034.
G.B. Hazen and A. Schwartz (2009), "Incorporating Extrinsic Goals into Decision and Cost-Effectiveness Analyses", Medical Decision Making 29 (5) 580-589.
G.B. Hazen (2007), "Adding Extrinsic Goals to the QALY Model", Decision Analysis 4 (1) 3-16.
G.B. Hazen and Min Huang (2006), "Parametric Sensitivity Analysis Using Large-Sample Approximate Bayesian Posterior Distributions",. Decision Analysis 3 (4) 208-219.
G.B. Hazen and Min Huang (2006), "Large-Sample Bayesian Posterior Distributions for Probabilistic Sensitivity Analysis", Medical Decision Making 26 (5), 512-534.
G.B. Hazen (2004), "Multiattribute Structure for QALYs", Decision Analysis 1 (4), 205-216.
J.C. Felli and G.B. Hazen (2004), "Javelin Diagrams: A Graphical Tool for Probabilistic Sensitivity Analysis", Decision Analysis 1 (2), 93-107.
G.B. Hazen (2003), "A New Perspective on Multiple Internal Rates of Return", The Engineering Economist 48, 31-51.
G.B. Hazen (2002) "Stochastic Trees and the StoTree Modeling Environment: Models and Software for Medical Decision Analysis", Journal of Medical Systems 26, 399-413.
G.B. Hazen (2000), "Preference Factoring for Stochastic Trees", Management Science 46, 389-403.
G.B. Hazen and J. Sounderpandian (1999), "Lottery Acquisition versus Information Acquisition: Prices and Preference Reversals" Journal of Risk and Uncertainty 18, 125-136.
J.C. Felli and G.B. Hazen, "Sensitivity Analysis and the Expected Value of Perfect Information", Medical Decision Making 18 (1998) 95-109.
Erratum Medical Decision Making 21 (2001) 254.
Erratum Medical Decision Making 23 (2003) 97.
G.B. Hazen and J.M. Pellissier, "Recursive Utility for Stochastic Trees", Operations Research 44 (1996) 788-809.
R.W. Chang, J.M. Pellissier and G.B. Hazen, "A Cost-Effectiveness Analysis of Total Hip Arthroplasty for Osteoarthritis of the Hip", Journal of the American Medical Association 275 (1996) 858-865.
G.B. Hazen, "Factored Stochastic Trees: A Tool for Solving Complex Temporal Medical Decision Models," Medical Decision Making. 13 (1993), 227-236.
G.B. Hazen, "Stochastic Trees: A New Technique for Temporal Medical Decision Modeling," Medical Decision Making 12 (1992) 163-178.
StoTree is software tool for the formulation and solution of continuous-time Markov models of medical interventions, implemented in the Excel spreadsheet environment. Although the popular package TreeAge from TreeAge Software Inc. has a more extensive set of tools, StoTree is a free alternative that can handle the same types of models in a continuous-time framework. Like Precision Tree from Palisade Corporation, StoTree is an Excel addin that can implement both decision trees and Markov models.
You can watch an introductory video about StoTree and its capabilities here.
This text has been used for over a decade in the introductory probability course IE 202 at Northwestern, and is now available in electronic form. See here for a summary of the unique features of the text.
This document presents strategies you can use to write an effective project report, and prescribes an organizational structure for writing such a report. Four fundamental objectives for writing an effective project report are cited, namely, demonstrate your familiarity with the problem, establish your modeling expertise, maximize reader insight, and minimize reader effort. Writing strategies and organizational structure are meant to secure these objectives.
An electronic version is available.
Josh McDowell's book Evidence That Demands a Verdict has been described as an authoritative defense of Christianity and a masterpiece of Christian apologetics that provides scholarly, intelligent, well-grounded answers to questions about the Christian faith. Here I report on my investigation of McDowell's claims.
Last updated August 2021