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The weighted priors approach for combining expert opinions in logistic regression experiments

Journal Article · · Quality Engineering
 [1];  [2];  [2]
  1. Pennsylvania State Univ., University Park, PA (United States). Dept. of Statistics
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
+ Show Author Affiliations
When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration. While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.
Research Organization:
Los Alamos National Laboratory (LANL)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1360704
Report Number(s):
LA-UR-16-24989
Journal Information:
Quality Engineering, Journal Name: Quality Engineering Journal Issue: 3 Vol. 29; ISSN 0898-2112
Publisher:
American Society for Quality ControlCopyright Statement
Country of Publication:
United States
Language:
English

References (8)

Optimal Bayesian design applied to logistic regression experiments journal February 1989
A Bayesian Model for Integrating Multiple Sources of Lifetime Information in System-Reliability Assessments journal April 2011
The Coordinate-Exchange Algorithm for Constructing Exact Optimal Experimental Designs journal February 1995
Experimental Design for Binary Data journal March 1983
Prediction of Reliability of an Arbitrary System from a Finite Population journal December 2010
Monte Carlo sampling methods using Markov chains and their applications journal April 1970
On the existence of maximum likelihood estimates in logistic regression models journal January 1984
Optimum Designs in Regression Problems journal June 1959

Cited By (1)

How to Host An Effective Data Competition: Statistical Advice for Competition Design and Analysis
  • Anderson‐Cook, Christine M.; Myers, Kary L.; Lu, Lu
  • Statistical Analysis and Data Mining: The ASA Data Science Journal, Vol. 12, Issue 4 https://doi.org/10.1002/sam.11404
journal February 2019

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Related Subjects

97 MATHEMATICS AND COMPUTING
Mathematics