Comparing the reliability of related populations with the probability of agreement
Journal Article
·
· Technometrics
- Univ. of San Francisco, San Francisco, CA (United States)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Combining information from different populations to improve precision, simplify future predictions, or improve underlying understanding of relationships can be advantageous when considering the reliability of several related sets of systems. Using the probability of agreement to help quantify the similarities of populations can help to give a realistic assessment of whether the systems have reliability that are sufficiently similar for practical purposes to be treated as a homogeneous population. In addition, the new method is described and illustrated with an example involving two generations of a complex system where the reliability is modeled using either a logistic or probit regression model. Note that supplementary materials including code, datasets, and added discussion are available online.
- Research Organization:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- DOD; USDOE
- Grant/Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1304827
- Report Number(s):
- LA-UR--15-27900
- Journal Information:
- Technometrics, Journal Name: Technometrics; ISSN 0040-1706
- Publisher:
- Taylor & FrancisCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Bayesian probability of predictive agreement for comparing the outcome of two separate regressions: Bayesian probability of predictive agreement for comparing the outcome of two separate regressions
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