One year to go before we open up the 2023 conference for the Society for Risk Analysis Europe in Lund.
Dates 18 to 21 June 2023
The theme of the conference is Risk and assessment in a changing world
Funding from The Crafoord Foundation is highly appreciated.
I have a poster at SETAC Copenhagen about Bayesian networks. My main message is that Bayesian networks should not be limited to specific applications of probabilistic graphical models, and that the term is currently confusing including both expert informed Bayesian Belief networks and data-driven Bayesian networks in machine learning. I do not see any reason why not Bayesian statistical models can not be seen as a Bayesian network. Widening the concept can benefit from the increasing uptake and positive response of Bayesian networks to support the need for flexible quantitative models in science and society. With this in mind, there are different modelling approaches able to do different things that are Bayesian networks. We then have to go back and describe what each approach actually does. What do I gain from this? Well. at least I am better off when we include any probabilistic graphical modelling into the concept of Bayesian network.
Check out my poster and talk part of the survey giving your perspective on what is (or is not) a Bayesian network.
Should We Reconsider or Upgrade Bayesian Networks for Environmental Assessments_poster_SETAC2022
The survey – link to google forms
Results can be seen here
Ivette’s work A robust Bayesian bias-adjusted random effects model for consideration of uncertainty about bias terms in evidence synthesis has been accepted for publication in Statistics in Medicine.
In this paper, we construct a set for the bias terms based on the qualitative information in a Cochrane risk of bias table. To accommodate the imprecision in bias terms, bias adjustment in a meta-analysis model is performed in a Robust Bayesian analysis framework which results in lower and upper bounds on the probability expressing uncertainty in quantities of interest.
Congratulations
Following the succes from 2021 we will continue with series of online talks as part of Bayes@Lund
Welcome to join
Organisers
Dmytro Perepolkin, Ullrika Sahlin, Rasums Bååth
Aubrey Clayton on Bernoulli’s Fallacy
February 3rd, 2022 at 16 CET on Zoom.
Abstract:
For as long as there has been statistical inference, practitioners have been confusing the probability of data-given-hypothesis and the probability of hypothesis-given-data, the “fallacy of the transposed conditional.” In this talk, I’ll survey the history of this mistake including recent examples in disparate fields, up to and including present-day orthodox statistical practice. I’ll argue that the fallacy represents a larger failure of thinking about probability–which I call “Bernoulli’s Fallacy”–and that the same error underlies much of the current crisis of replication in science. Finally, I’ll share thoughts about what we should do to ensure the statistical methods of the future are built on a solid foundation.
I have a postdoc position open for someone interested in the assessment of overall uncertainty in risk assessment. It is part of a H2020 project about new methodologies for human risk assessment (Riskhun3r). The candidate will be working with uncertainty analyses for chemical and human health risk assessment, but I don’t require prior knowledge about these types of assessments. We want someone with a degree in mathematics or statistics or similar, with knowledge about Bayesian inference and an interest in subjective probability as a measure for epistemic uncertainty.
Read more and apply before Jan 13 2022
Note, I get a lot of applications from candidates doing fuzzy numbers, but this is not a measure we will look at in this postdoc. This research is about the use of subjective probability to quantify uncertainty.
Contact me ullrika.sahlin [at] cec.lu.se if you want to know more.
2021 is coming to an end and it is with deligth I conclude that two PhD students in the Uncertainty and Evidence Lab research group has finalised and successfully defended their theses. Maria Blasi Romero’s thesis Wild bees in agricultural landscapes: Modelling land use and climate effects across space and time and Ivette Raices Cruz’s thesis on Robust analysis of uncertainty in scientific assessments wraps up some of our research from the last four years.
Now we turn the page and go into 2022 with new adventures.
On Friday 17 December at 13:00, Ivette Raices Cruz defends her doctoral thesis in Environmental Science entitled ‘Robust analysis of uncertainty in scientific assessments’.
The Faculty opponent is Professor Mark E. Borsuk from Duke University, USA.
Read more and sign up here to attend via link
The application for the graduate course Bayesian Analysis and Decision Theory (NAMV005, 5 credits) is now open!
This year we do 5 meetings in January-February (four of them online and the last one on campus in Lund). PhD students, who are part of the ClimBECO research school will be given priority, but we welcome students from other research schools, as well. The course introduces Bayesian analysis using Stan (for MCMC sampling) and R (as an interface to Stan and a data analysis platform). The major part of the course covers Bayesian data analysis and statistical inference. We also put Bayesian analysis into the context related to subjective probability to quantify uncertainty and Bayesian decision theory. Application is open until 24th of December or when the spots are filled (whichever comes first). More information about the course and a link to the registration form can be found at https://canvas.education.lu.se/courses/5146
Welcome
Ullrika Sahlin and Dmytro Perepolkin
Centre for Environmental and Climate Sciences, Lund University
We encourage you to submit an abstract to and/or spread the word about the session Expert Knowledge Elicitation in environmental assessments – subjective, but scientific (Track 4-Ecological Risk Assessment and Human Health Risk Assessment of chemicals, other stressors and mixtures) at the forthcoming Society of Environmental Toxicology and Chemistry (SETAC) meeting in Copenhagen, in May 2022 (https://europe2022.setac.org ).
This will be an opportunity to share and discuss recent advances in expert knowledge elicitations and how such elicitations can support risk assessment. It will also be an opportunity to introduce expert elicitation as a scientific method to the wider community of SETAC.
The abstract submission deadline is 1 December 2021. Abstracts should be submitted via the online submission page https://europe2022.setac.org
We look forward to receiving your contribution!
Ullrika Sahlin, Anca Hanea and Dmytro Perepolkin (Session chairs)
Session abstract
Expert Knowledge Elicitation (a.k.a. Structured Expert Judgement) is a formal process for eliciting and combining judgments from subject-matter experts about the relevant quantities in scientific assessments. Expert opinion and judgment are used in statistical modelling and inference (e.g., as parameter estimates or as priors in Bayesian inference) and decision-making. Elicited judgments about an uncertain quantity often take the form of a subjective probability distribution for that quantity. If judgments are obtained from several experts, they may need to be combined, unless the experts reach consensus.
The quality of the elicited data may be hampered by the experts’ limited experience with making probabilistic judgements and/or the poor use of elicitation protocols in practical applications. Because humans are prone to cognitive biases, logical errors and social influences (e.g., peer pressure) when making (probabilistic) judgements, formal Expert Knowledge Elicitation protocols have been designed to address and minimize these effects. Expert Knowledge Elicitation has been used for a long time, and is increasingly being used to fill data gaps and to quantify uncertainty. Disciplined and consistent elicitation based on scientific insight from cognitive psychology and probability theory, combined with the domain knowledge and practical experience in environmental assessment can turn subjective judgements into a solid scientific basis for making policy recommendations and assessing relevant risks.
The purpose of this session is to revisit the methodological framework and to bring up the recent advances within the Expert Knowledge Elicitation, particularly focusing on its usefulness for environmental assessment. We welcome contributions on methodological topics such as :
We also welcome contributions about any other recent developments to strengthen the use and scientific rigour of Expert Knowledge Elicitation when used for assessment.
Join the Swedish Society for Risk Sciences and the Nordic chapter of the Society for Risk Analysis’ upcoming webinar entitled RISKUT2021 on October 21, 2021.
RISKUT2021 is a half-day online conference about teaching risk. This webinar will offer group discussions on the theme “the risk curriculum.” The aim of the conference is to create a meeting place for sharing ideas and experiences on how to educate about risk. Individuals from academia, the public and private sector and from all levels of education are invited.
The conference language will be English and this event is free of charge.
More information and how to sign up
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