Results 61 to 70 of about 242,378 (342)

On Bayes Factor Functions

Bayesian Analysis
We describe Bayes factors functions based on the sampling distributions of \emph{z}, \emph{t}, $χ^2$, and \emph{F} statistics, using a class of inverse-moment prior distributions to define alternative hypotheses. These non-local alternative prior distributions are centered on standardized effects, which serve as indices for the Bayes factor function ...
Datta, Saptati, Guha, Riana, Shudde, Rachael, Johnson, Valen E.   +3 more
openaire   +2 more sources

Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito, Chiara Meneghini, Alice Galli, Luca Gallo, Pierfrancesco Mitrotti, Paola Dimartino, Marianna Inglese, Cinzia Zatti, Alessandro Lupini, Andrea Pilotto, Alessandro Padovani, Micol Avenali, Enza Maria Valente, Cristina Tassorelli, Silvia P. Caminiti   +14 more
wiley   +1 more source

Sparse Portfolio selection via Bayesian Multiple testing

, 2020
We presented Bayesian portfolio selection strategy, via the $k$ factor asset pricing model. If the market is information efficient, the proposed strategy will mimic the market; otherwise, the strategy will outperform the market.
Das, Sourish, Sen, Rituparna
core  

Bayes factors and the geometry of discrete hierarchical loglinear models

, 2011
A standard tool for model selection in a Bayesian framework is the Bayes factor which compares the marginal likelihood of the data under two given different models.
Letac, Gerard, Massam, Helene
core   +3 more sources

Reperfusion‐Dependent Outcomes After Endovascular Thrombectomy Stratified by NIHSS‐ASPECTS Clinical‐Core Mismatch

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective This analysis evaluates the effect of successful reperfusion on functional outcomes after MT, stratified by admission National Institutes of Health Stroke Scale (NIHSS) and Alberta Stroke Program Early CT Score (ASPECTS) as surrogates for clinical‐core mismatch, using multicenter registry data.
Felix Schlicht, Lukas Meyer, Gabriel Broocks, Matthias Bechstein, Christian Thaler, Christian Heitkamp, Laurens Winkelmeier, Vincent Geest, Alexander Heitkamp, Maximilian Jungnitz, Gregor Peter, Luca Meucci, Tobias Faizy, Jawed Nawabi, Caspar Brekenfeld, Fabian Flottmann, Maximilian Schell, Alexandros Hadjilaou, Uta Hanning, Götz Thomalla, Jens Fiehler, Susanne Gellißen, Helge C. Kniep, for the German Stroke Registry Endovascular Treatment, (GSR‐ET) Alexander Nave, Anna Alegiani, Annerose Mengel, Arno Reich, Bernd Eckert, Charlotte Pietrock, Christian Nolte, Eberhard Siebert, Fabian Flottmann, Fee Keil, Franziska Dorn, Gabor Petzold, Götz Thomalla, Hanna Zimmermann, Jan Borggrefe, Jan Hendrik Schäfer, Jens Fiehler, Joachim Röther, Klaus Gröschel, Lars Kellert, Mario Abruscato, Maximilian Schell, Omid Nikoubashman, Peter Schellinger, Silke Wunderlich, Steffen Tiedt, Sven Thonke, Timo Uphaus, Tobias Boeckh‐Behrens, Ulrike Ernemann   +53 more
wiley   +1 more source

Bayes factor for testing between different structures of random genetic groups: A case study using weaning weight in Bruna dels Pirineus beef cattle

Genetics Selection Evolution, 2007
The implementation of genetic groups in BLUP evaluations accounts for different expectations of breeding values in base animals. Notwithstanding, many feasible structures of genetic groups exist and there are no analytical tools described to compare them
Varona Luis, Piedrafita Jesús, Casellas Joaquim   +2 more
doaj   +1 more source

Using Bayes to get the most out of non-significant results [PDF]

, 2014
No scientific conclusion follows automatically from a statistically non-significant result, yet people routinely use non-significant results to guide conclusions about the status of theories (or the effectiveness of practices).
Allen, Armitage, Armstrong, Baguley, Baguley, Baguley, Berger, Berger, Berry, Berry, Box, Buhle, Burnham, Button, Cohen, Cohen, Cohen, Cohen, Cumming, Dienes, Dienes, Dienes, Dienes, Dienes, Dienes, Edwards, Elliot, Faul, Fisher, Freedman, Fu, Fu, Gallistel, Glover, Goodman, Greenwald, Greenwald, Guo, Guo, Hodges, Hoijtink, Howard, Howson, Jackman, Jaynes, Jeffreys, Kass, Kievit, Kirsch, Kirsch, Kiyokawa, Kruschke, Kruschke, Kruschke, Kruschke, Kruschke, Kruschke, Lee, Lee, Lewis, Liang, Lindley, Lindley, Lockhart, Mayo, McGrayne, McLatchie, Mealor, Mealor, Mealor, Morey, Newell, Nuijten, Oakes, Parris, Pashler, Raz, Rogers, Rosenthal, Rosenthal, Rouder, Rouder, Rouder, Rouder, Rouder, Royall, Sagarin, Sanborn, Sedlmeier, Semmens-Wheeler, Serlin, Shang, Smith, Smithson, Song, Stone, Storm, Strube, Tan, Tan, Terhune, Vanpaemel, Vanpaemel, Verhagen, Wagenmakers, Wagenmakers, Watson, Wetzels, Wetzels, Wetzels, Wetzels, Wilcox, Yu, Yuan   +113 more
core   +2 more sources

Bayes factor consistency

, 2016
Good large sample performance is typically a minimum requirement of any model selection criterion. This article focuses on the consistency property of the Bayes factor, a commonly used model comparison tool, which has experienced a recent surge of attention in the literature. We thoroughly review existing results. As there exists such a wide variety of
Chib, Siddhartha, Kuffner, Todd A.
openaire   +2 more sources

Testing theories with Bayes factors

, 2021
Bayes factors are a useful tool for researchers in the behavioural and social sciences, partly because they can provide evidence for no effect relative to the sort of effect expected. By contrast, a non-significant result does not provide evidence for the H0 tested.
openaire   +2 more sources

Is Young's Modulus a Critical Coating Property Determining Fouling‐Release Performance of Marine Coatings?

Advanced Engineering Materials, EarlyView.
The release of foulers from protective marine coatings is determined by several interrelated material properties, including the strength of Young's modulus, the flexibility of chain segments, the surface free energy, and the magnitude of hydrodynamic stress.
Johann C. Schaal, Andreas Brinkmann, Andreas Hartwig   +2 more
wiley   +1 more source