Bayesian model-averaged meta-analysis in medicine.
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DOI: 10.1002/sim.9170
Abstract: We outline a Bayesian model-averaged (BMA) meta-analysis for standardized mean differences in order to quantify evidence for both treatment effectiveness δ and across-study heterogeneity τ . We construct four competing models by orthogonally combining two… read more here.
Keywords: medicine; bayesian model; prior distributions; meta analysis ... See more keywords
DERIVING ROBUST BAYESIAN PREMIUMS UNDER BANDS OF PRIOR DISTRIBUTIONS WITH APPLICATIONS
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DOI: 10.1017/asb.2018.36
Abstract: Abstract We study the propagation of uncertainty from a class of priors introduced by Arias-Nicolás et al. [(2016) Bayesian Analysis, 11(4), 1107–1136] to the premiums (both the collective and the Bayesian), for a wide family… read more here.
Keywords: bands prior; bayesian premiums; deriving robust; robust bayesian ... See more keywords
A cerebellar mechanism for learning prior distributions of time intervals
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DOI: 10.1038/s41467-017-02516-x
Abstract: Knowledge about the statistical regularities of the world is essential for cognitive and sensorimotor function. In the domain of timing, prior statistics are crucial for optimal prediction, adaptation and planning. Where and how the nervous… read more here.
Keywords: cerebellar mechanism; time intervals; time; distributions time ... See more keywords
Catalytic prior distributions with application to generalized linear models
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DOI: 10.1073/pnas.1920913117
Abstract: Significance We propose a strategy for building prior distributions that stabilize the estimation of complex “working models” when sample sizes are too small for standard statistical analysis. The stabilization is achieved by supplementing the observed… read more here.
Keywords: estimation; catalytic prior; generalized linear; model ... See more keywords
Inferring prior distributions of recruitment compensation metrics from life-history parameters and allometries
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DOI: 10.1139/cjfas-2018-0463
Abstract: The recruitment compensation metrics, the stock–recruit steepness (h) and compensation ratio (κ), are difficult to estimate, yet they are integral components of contemporary fishery models. To aid ... read more here.
Keywords: inferring prior; distributions recruitment; prior distributions; compensation metrics ... See more keywords
Dangers of the Defaults: A Tutorial on the Impact of Default Priors When Using Bayesian SEM With Small Samples
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DOI: 10.3389/fpsyg.2020.611963
Abstract: When Bayesian estimation is used to analyze Structural Equation Models (SEMs), prior distributions need to be specified for all parameters in the model. Many popular software programs offer default prior distributions, which is helpful for… read more here.
Keywords: small samples; default; bayesian sem; default priors ... See more keywords