Prior and Posterior Linear Pooling for Combining Expert Opinions: Uses and Impact on Bayesian Networks—The Case of the Wayfinding Model

Article


Farr, Charisse, Ruggeri, Fabrizio and Mengersen, Kerrie. 2018. "Prior and Posterior Linear Pooling for Combining Expert Opinions: Uses and Impact on Bayesian Networks—The Case of the Wayfinding Model." Entropy: international and interdisciplinary journal of entropy and information studies. 20 (3), pp. 1-14. https://doi.org/10.3390/e20030209
Article Title

Prior and Posterior Linear Pooling for Combining Expert Opinions: Uses and Impact on Bayesian Networks—The Case of the Wayfinding Model

ERA Journal ID39951
Article CategoryArticle
AuthorsFarr, Charisse (Author), Ruggeri, Fabrizio (Author) and Mengersen, Kerrie (Author)
Journal TitleEntropy: international and interdisciplinary journal of entropy and information studies
Journal Citation20 (3), pp. 1-14
Article Number209
Number of Pages14
Year2018
Place of PublicationSwitzerland
ISSN1099-4300
Digital Object Identifier (DOI)https://doi.org/10.3390/e20030209
Web Address (URL)https://www.mdpi.com/1099-4300/20/3/209
Abstract

The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions and then places them into the BN, is a common method. This paper considers this approach and an alternative pooling method, Posterior Linear Pooling (PoLP). The PoLP method constructs a BN for each expert, and then pools the resulting probabilities at the nodes of interest. The advantages and disadvantages of these two methods are identified and compared and the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behavior of different groups of people and how these different methods may be able to capture such differences. The paper focusses on six nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (Female, Male), Travel Experience (Experienced, Inexperienced), and Travel Purpose (Business, Personal), and finds that different behaviors can indeed be captured by the different methods.

Keywordsbayesian networks; linear pooling; posterior pooling; prior pooling; wayfinding; expert opinions
ANZSRC Field of Research 2020490501. Applied statistics
Byline AffiliationsQueensland University of Technology
Institute of Applied Mathematics and Information Technologies, Italy
Institution of OriginUniversity of Southern Queensland
Permalink -

https://research.usq.edu.au/item/q525v/prior-and-posterior-linear-pooling-for-combining-expert-opinions-uses-and-impact-on-bayesian-networks-the-case-of-the-wayfinding-model

Download files


Published Version
2018_FarrRugerriMengersen_Entropy.pdf
License: CC BY 4.0
File access level: Anyone

  • 189
    total views
  • 97
    total downloads
  • 1
    views this month
  • 1
    downloads this month

Export as

Related outputs

Geographical and spatial variations in bowel cancer screening participation, Australia, 2015–2020
Dasgupta, Paramita, Cameron, Jessica K., Goodwin, Belinda, Cramb, Susanna M., Mengersen, Kerrie, Aitken, Joanne F. and Baade, Peter D.. 2023. "Geographical and spatial variations in bowel cancer screening participation, Australia, 2015–2020." PLoS One. 18 (7). https://doi.org/10.1371/journal.pone.0288992
Geographical and spatial disparities in the incidence and survival of rare cancers in Australia
Dasgupta, Paramita, Cameron, Jessica K., Cramb, Susanna M., Trevithick, Richard W., Aitken, Joanne F., Mengersen, Kerrie and Baade, Peter D.. 2023. "Geographical and spatial disparities in the incidence and survival of rare cancers in Australia." International Journal of Cancer. 152 (8), pp. 1601-1612. https://doi.org/10.1002/ijc.34395
Geographic distribution of malignant mesothelioma incidence and survival in Australia
Cameron, Jessica K., Aitken, Joanne, Reid, Alison, Mengersen, Kerrie, Cramb, Susanna, Preston, Paige, Armstrong, Bruce and Baade, Peter. 2022. "Geographic distribution of malignant mesothelioma incidence and survival in Australia." Lung Cancer. 167, pp. 17-24. https://doi.org/10.1016/j.lungcan.2022.03.017
An intuitive dashboard for Bayesian Network inference
Reddy, Vikas, Farr, Anna Charisse, Wu, Paul, Mengersen, Kerrie and Yarlagadda, Prasad K. D. V.. 2014. "An intuitive dashboard for Bayesian Network inference." 2nd International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE 2013). Prague, Czech Republic 01 - 05 Sep 2013 Bristol, United Kingdom. https://doi.org/10.1088/1742-6596/490/1/012023
Combining Opinions for Use in Bayesian Networks: A Measurement Error Approach
Farr, A. Charisse, Mengersen, Kerrie, Ruggeri, Fabrizio, Simpson, Daniel, Wu, Paul and Yarlagadda, Prasad. 2020. "Combining Opinions for Use in Bayesian Networks: A Measurement Error Approach." International Statistical Review. 88 (2), pp. 335-353. https://doi.org/10.1111/insr.12350
Factors affecting timely completion of a PhD: a complex systems approach
Pitchforth, Jegar, Beames, Stephanie, Thomas, Aleysha, Falk, Matthew, Farr, Charisse, Gasson, Susan, Thamrin, Sri Astuti and Mengersen, Kerrie. 2012. "Factors affecting timely completion of a PhD: a complex systems approach." Journal of the Scholarship of Teaching and Learning. 12 (4), pp. 124-135.
A mathematical model of Chlamydial infection incorporating movement of Chlamydial particles
Mallet, D. G., Bagher-Oskouei, M., Farr, A. C., Simpson, D. P. and Sutton, K. J.. 2013. "A mathematical model of Chlamydial infection incorporating movement of Chlamydial particles." Bulletin of Mathematical Biology. 75 (11), pp. 2257-2270. https://doi.org/10.1007/s11538-013-9891-9
Wayfinding: a simple concept, a complex process
Farr, Anna Charisse, Kleinschmidt, Tristan, Yarlagadda, Prasad and Mengersen, Kerrie. 2012. "Wayfinding: a simple concept, a complex process." Transport Reviews. 32 (6), pp. 715-743. https://doi.org/10.1080/01441647.2012.712555
Factors Influencing the Success of Culturally and Linguistically Diverse Students in Engineering and Information Technology
Yarlagadda, Prasad KDV, Sharma, Jyoti, Silva, Pujitha, Woodman, Karen, Pitchforth, Jegar and Mengersen, Kerrie. 2018. "Factors Influencing the Success of Culturally and Linguistically Diverse Students in Engineering and Information Technology." International Journal of Engineering Education. 34 (4), pp. 1384-1399.
A Bayesian Network-based customer satisfaction model: a tool for management decisions in railway transport
Chakraborty, Subrata, Mengersen, Kerrie, Fidge, Colin, Ma, Lin and Lassen, David. 2016. "A Bayesian Network-based customer satisfaction model: a tool for management decisions in railway transport." Decision Analytics. 3 (4), pp. 1-24. https://doi.org/10.1186/s40165-016-0021-2
Multifaceted modelling of complex business enterprises
Chakraborty, Subrata, Mengersen, Kerrie, Fidge, Colin, Ma, Lin and Lassen, David. 2015. "Multifaceted modelling of complex business enterprises." PLoS One. 10 (8). https://doi.org/10.1371/journal.pone.0134052
Investigating effective wayfinding in airports: a Bayesian Network approach
Farr, Anna Charisse, Kleinschmidt, Tristan, Johnson, Sandra, Yarlagadda, Prasad and Mengersen, Kerrie. 2014. "Investigating effective wayfinding in airports: a Bayesian Network approach." Transport. 29 (1), pp. 90-99. https://doi.org/10.3846/16484142.2014.898695