First Advisor

Harold A. Linstone

Term of Graduation

Spring 1976

Date of Publication


Document Type


Degree Name

Doctor of Philosophy (Ph.D.) in Systems Science


Systems Science




Expert Evidence, Bayesian statistical decision theory, Decision making



Physical Description

1 online resource (v, 111 pages)


Subjective information is a valuable resource; however, decisionmakers often ignore it because of difficulties in eliciting it from assessors. This thesis is on Bayesian inquiry and it presents an approach to eliciting subjective information from assessors. Based on the concepts of cascaded inference and Bayesian statistics, the approach is designed to reveal to the decision-maker the way in which the assessor considers his options and the reasons he has for selecting particular alternatives. Unlike previous works on cascaded inferences, the approach here focuses on incoherency. Specifically, it employs the use of additional information to revise and check the estimates. The reassessment may be done directly or indirectly. The indirect procedure uses a second order probability or type II distribution. An algorithm utilizing this approach is also presented. The methodology is applicable to any number of assessors. Procedures for aggregating and deriving surrogate distributions are also proposed.


© 1976 King Gee Lee

In Copyright. URI: This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).


If you are the rightful copyright holder of this dissertation or thesis and wish to have it removed from the Open Access Collection, please submit a request to and include clear identification of the work, preferably with URL.

Persistent Identifier