Results 1 to 10 of about 50,404 (163)

Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models [PDF]

NeuroImage, 2022
The potential of normative modeling to make individualized predictions from neuroimaging data has enabled inferences that go beyond the case-control approach.
Johanna M.M. Bayer, Richard Dinga, Seyed Mostafa Kia, Akhil R. Kottaram, Thomas Wolfers, Jinglei Lv, Andrew Zalesky, Lianne Schmaal, Andre Marquand   +8 more
doaj   +4 more sources

Recalibrating single-study effect sizes using hierarchical Bayesian models [PDF]

Frontiers in Neuroimaging, 2023
IntroductionThere are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to
Zhipeng Cao, Zhipeng Cao, Matthew McCabe, Peter Callas, Renata B. Cupertino, Jonatan Ottino-González, Alistair Murphy, Devarshi Pancholi, Nathan Schwab, Orr Catherine, Kent Hutchison, Janna Cousijn, Alain Dagher, John J. Foxe, Anna E. Goudriaan, Robert Hester, Chiang-Shan R. Li, Wesley K. Thompson, Angelica M. Morales, Edythe D. London, Valentina Lorenzetti, Maartje Luijten, Rocio Martin-Santos, Reza Momenan, Martin P. Paulus, Martin P. Paulus, Lianne Schmaal, Lianne Schmaal, Rajita Sinha, Nadia Solowij, Dan J. Stein, Elliot A. Stein, Anne Uhlmann, Ruth J. van Holst, Dick J. Veltman, Reinout W. Wiers, Murat Yücel, Sheng Zhang, Patricia Conrod, Scott Mackey, Hugh Garavan, The ENIGMA Addiction Working Group   +41 more
doaj   +2 more sources

Hierarchical Graphical Bayesian Models in Psychology

Revista Colombiana de Estadística, 2014
The improvement of graphical methods in psychological research can promote their use and a better comprehension of their expressive power. The application of hierarchical Bayesian graphical models has recently become more frequent in psychological ...
GUILLERMO CAMPITELLI, GUILLERMO MACBETH
doaj   +6 more sources

Sensitivity Analysis for Bayesian Hierarchical Models

Bayesian Analysis, 2015
Prior sensitivity examination plays an important role in applied Bayesian analyses. This is especially true for Bayesian hierarchical models, where interpretability of the parameters within deeper layers in the hierarchy becomes challenging. In addition, lack of information together with identifiability issues may imply that the prior distributions for
Malgorzata Roos, Leonhard Held, Håvard Rue   +2 more
exaly   +5 more sources

A dynamic hierarchical Bayesian approach for forecasting vegetation condition [PDF]

Natural Hazards and Earth System Sciences, 2022
Agricultural drought, which occurs due to a significant reduction in the moisture required for vegetation growth, is the most complex amongst all drought categories.
E. E. Salakpi, P. D. Hurley, P. D. Hurley, J. M. Muthoka, A. Bowell, A. Bowell, S. Oliver, S. Oliver, P. Rowhani   +8 more
doaj   +1 more source

A Bayesian Hierarchical Model for Criminal Investigations [PDF]

Bayesian Analysis, 2021
Potential violent criminals will often need to go through a sequence of preparatory steps before they can execute their plans. During this escalation process police have the opportunity to evaluate the threat posed by such people through what they know, observe and learn from intelligence reports about their activities.
Bunnin, F. O., Smith, J. Q.
openaire   +3 more sources

Bayesian Hierarchical Modeling: An Introduction and Reassessment

Behavior Research Methods, 2022
With the recent development of easy-to-use tools for Bayesian analysis, psychologists have started to embrace Bayesian hierarchical modeling. Bayesian hierarchical models provide an intuitive account of inter- and intraindividual variability and are particularly suited for the evaluation of repeated-measures designs. Here, we provide guidance for model
Myrthe Veenman, Angelika Marlene Stefan, Julia M. Haaf   +2 more
openaire   +4 more sources

Hierarchical change-point regression models including random effects to estimate empirical critical loads for nitrogen using Bayesian Regression Models (brms) and JAGS

MethodsX, 2022
The concept of critical loads is used in the framework of the Convention on Long-range Transboundary Air Pollution (UNECE) to define thresholds below which no damaging effects on habitats occur based on the latest scientific knowledge.
Tobias Roth, Simon Tresch, Enzai Du, Sabine Braun   +3 more
doaj   +1 more source

A Hierarchical Bayesian Model of Adaptive Teaching

Cognitive Science, 2022
Abstract How do teachers learn about what learners already know? How do learners aid teachers by providing them with information about their background knowledge and what they find confusing? We formalize this collaborative reasoning process using a hierarchical Bayesian model of pedagogy.
Alicia M. Chen, Andrew Palacci, Natalia Vélez, Robert D. Hawkins, Samuel J. Gershman   +4 more
openaire   +2 more sources

Hierarchical Bayesian Modeling of Pharmacophores in Bioinformatics [PDF]

Biometrics, 2010
One of the key ingredients in drug discovery is the derivation of conceptual templates called pharmacophores. A pharmacophore model characterizes the physicochemical properties common to all active molecules, called ligands, bound to a particular protein receptor, together with their relative spatial arrangement. Motivated by this important application,
Mardia, KV, Nyirongo, VB, Fallaize, CJ, Barber, S, Jackson, RM   +4 more
openaire   +4 more sources