Ruberu et al. (2023) introduce an elegant approach to fit a complicated meta-analysis problem with diverse reporting modalities into the framework of hierarchical Bayesian inference. We discuss issues related to some of the involved parametric model assumptions.
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http://dx.doi.org/10.1093/biomtc/ujae042 | DOI Listing |
Alzheimers Dement
December 2024
Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), site Rostock / Greifswald, Rostock, Germany.
Background: Familial Alzheimer's disease research necessitates innovative methodologies to disentangle the intricate relationships between genetic factors and neuroimaging measures. Traditional frequentist approaches, often hampered by small sample sizes in this population and challenges in incorporating prior knowledge transparently, may limit the robustness of findings.
Methods: We analyzed neuroimaging data of preclinical PSNE1 single mutation carriers, utilizing the software JASP to test effects of carrier status on measures of basal forebrain functional connectivity using both frequentist and Bayesian approach.
Psychon Bull Rev
January 2025
Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
A variety of different evidence-accumulation models (EAMs) account for common response time and accuracy patterns in two-alternative forced choice tasks by assuming that subjects collect and sum information from their environment until a response threshold is reached. Estimates of model parameters mapped to components of this decision process can be used to explain the causes of observed behavior. However, such explanations are only meaningful when parameters can be identified, that is, when their values can be uniquely estimated from data generated by the model.
View Article and Find Full Text PDFPsychon Bull Rev
January 2025
Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France.
It is striking that visual attention, the process by which attentional resources are allocated in the visual field so as to locally enhance visual perception, is a pervasive component of models of eye movements in reading, but is seldom considered in models of isolated word recognition. We describe BRAID, a new Bayesian word-Recognition model with Attention, Interference and Dynamics. As most of its predecessors, BRAID incorporates three sensory, perceptual, and orthographic knowledge layers together with a lexical membership submodel.
View Article and Find Full Text PDFFront Hum Neurosci
December 2024
Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands.
Introduction: As brain-computer interfacing (BCI) systems transition fromassistive technology to more diverse applications, their speed, reliability, and user experience become increasingly important. Dynamic stopping methods enhance BCI system speed by deciding at any moment whether to output a result or wait for more information. Such approach leverages trial variance, allowing good trials to be detected earlier, thereby speeding up the process without significantly compromising accuracy.
View Article and Find Full Text PDFPharmacoepidemiol Drug Saf
January 2025
Hunan Institute for Drug Control, Changsha, Hunan, China.
Background And Objectives: Based on the Adverse Event Reporting System (FAERS) data from the US FDA, this study mined the adverse drug reactions of obeticholic acid (OCA) in the real world and provided reference for clinical safe drug use.
Methods: Adverse event reports for OCA from the second quarter of 2016 to the third quarter of 2023 were extracted. The analysis for adverse reaction signal detection was conducted using reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker methods.
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