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, 2023 The is no other model or hypothesis verification tool in Bayesian statistics that is as widely used as the Bayes factor. We focus on generative models that are likelihood-free and, therefore, render the computation of Bayes factors (marginal likelihood ratios) far from obvious. We propose a deep learning estimator of the Bayes factor based on simulated
Kim, Jungeum, Rockova, Veronika
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Bayes Factors for Mixed Models: a Discussion
Computational Brain & Behavior, 2022 Abstractvan Doorn et al. (2021) outlined various questions that arise when conducting Bayesian model comparison for mixed effects models. Seven response articles offered their own perspective on the preferred setup for mixed model comparison, on the most appropriate specification of prior distributions, and on the desirability of default ...
Johnny van Doorn +29 more
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Statistical Theory and Related Fields, 2020 The power-expected-posterior prior is used in this paper for comparing nested linear models. The asymptotic behaviour of the method is investigated for different values of the power parameter of the prior.
D. Fouskakis +2 more
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Replication Bayes factors from evidence updating [PDF]
Behavior Research Methods, 2017 We describe a general method that allows experimenters to quantify the evidence from the data of a direct replication attempt given data already acquired from an original study. These so-called replication Bayes factors are a reconceptualization of the ones introduced by Verhagen and Wagenmakers (2014) for the common t-test. This reconceptualization is
Marsman, Maarten +4 more
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Appreciating the Significance of Non-significant Findings in Psychology
Journal of European Psychology Students, 2019 Statistical hypothesis tests for which the null hypothesis cannot be rejected ("null findings") are often seen as negative outcomes in the life and social sciences and are thus scarcely published. Null findings can, however, bear important insights about
David M. A. Mehler +2 more
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Frontiers in Plant Science, 2017 Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods.
Jean-Baptiste Durand +7 more
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Introduction and evolution of dengue virus type 2 in Pakistan: a phylogeographic analysis [PDF]
, 2015 Discrete Bayes Factors from SPREAD. Locations are denoted with two letter codes (Additional file 5: Table S3). The upper half of the matrix shows the mean (standard deviation) for the discrete Bayes Factor calculated for the 12 discrete trait models. The
Amanda Sue +8 more
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Evaluating Manifest Monotonicity Using Bayes Factors [PDF]
Psychometrika, 2015 The assumption of latent monotonicity in item response theory models for dichotomous data cannot be evaluated directly, but observable consequences such as manifest monotonicity facilitate the assessment of latent monotonicity in real data. Standard methods for evaluating manifest monotonicity typically produce a test statistic that is geared toward ...
Tijmstra, Jesper +2 more
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European Journal of Psychotraumatology, 2017 Threat conditioning procedures have allowed the experimental investigation of the pathogenesis of Post-Traumatic Stress Disorder. The findings of these procedures have also provided stable foundations for the development of relevant intervention programs (
Angelos-Miltiadis Krypotos +2 more
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Open Physics, 2023 Accelerated or partially accelerated life tests are particularly significant in life testing experiments since they save time and cost. Partially accelerated life tests are carried out when the data from accelerated life testing cannot be extrapolated to
Al Mutairi Aned +5 more
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