Expert Elicitation Method Selection Process and Method Comparison
Research on integrative modeling has gained considerable attention in recent years and expert opinion has been increasingly recognized as an important data source and modeling contributor. However, little research has systematically compared and evaluated expert elicitation methods in terms of their ability to link with computational models that capture human behavior and social phenomena. In this paper, we describe a decision-making process we used for evaluating and selecting a task specific elicitation method within the framework of integrative computational social-behavioral modeling. From the existing literature, we identified the characteristics of problems that each candidate method is well suited to address. A small scale expert elicitation was also conducted to evaluate the comparative strength and weaknesses of the methods against a number of consensus-based decision criteria. By developing a set of explicit method evaluation criteria and a description characterizing decision problems for the candidate methods, we seek to gain a better understanding of the feasibility and costeffectiveness of integrating elicitation methods with computational modeling techniques. This serves an important first step toward expanding our research effort and trajectory toward greater interdisciplinary modeling research of human behavior.
|Date of creation:||Sep 2010|
|Contact details of provider:|| Postal: Piazza San Francesco 7, 53100 Siena|
Web page: http://www.depfid.unisi.it/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Justin Wolfers & Eric Zitzewitz, 2004.
NBER Working Papers
10504, National Bureau of Economic Research, Inc.
- Dewispelare, Aaron R. & Herren, L. Tandy & Clemen, Robert T., 1995. "The use of probability elicitation in the high-level nuclear waste regulation program," International Journal of Forecasting, Elsevier, vol. 11(1), pages 5-24, March.
When requesting a correction, please mention this item's handle: RePEc:usi:labsit:030. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alessandro Innocenti)
If references are entirely missing, you can add them using this form.