Results 61 to 70 of about 4,246,376 (189)
Empirical Bayes factors for common hypothesis tests.
PLoS ONEBayes factors for composite hypotheses have difficulty in encoding vague prior knowledge, as improper priors cannot be used and objective priors may be subjectively unreasonable.
Frank Dudbridge
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Bayesian Reanalysis of Statistically Nonsignificant Outcomes in Plastic Surgery Clinical Trials
Plastic and Reconstructive Surgery, Global OpenBackground:. Statistically nonsignificant randomized clinical trial (RCT) results are challenging to interpret, as they are unable to prove the absence of a difference between treatment groups.
Gordon C. Wong, MBBS, MRCS +5 more
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Bayes factor between Student
Genetics Selection Evolution, 2008 The implementation of Student t mixed models in animal breeding has been suggested as a useful statistical tool to effectively mute the impact of preferential treatment or other sources of outliers in field data. Nevertheless, these additional sources of
García-Cortés Luis +3 more
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Simpson’s Paradox and the Bayes Factor
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1998 Summary A counter-example presented by Lindley to Aitkin’s posterior Bayes factor is examined. The paradoxical feature of the counter-example is found to be a simple case of Simpson’s paradox.
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Bayes, Neyman and Neyman-Bayes Inference for Queueing Systems [PDF]
In this paper we will use the Bayesian inference for the parameters that appear in the queueing systems. We will estimate these parameters and we will build confidence intervals and significance tests for them, considering the parameters of the ...
Ciuiu, Daniel
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Optimal Track Fusion Using Bayes Factors
, 1999 In deciding whether to associate and fuse a group of tracks sent from independent local trackers, use should be made of all the data supporting them during theircommon history.
Mehmet Karan +3 more
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From Empirical Bayes to Full Bayes: Methods for Analyzubg Traffic Safey Data, October 25, 2004 [PDF]
, 2004 Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively ...
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Diagnosing the Misuse of the Bayes Factor in Applied Research
Advances in Methods and Practices in Psychological ScienceHypothesis testing is often used for inference in the social sciences. In particular, null hypothesis significance testing (NHST) and its p value have been ubiquitous in published research for decades. Much more recently, null hypothesis Bayesian testing
Jorge N. Tendeiro +4 more
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Introduction to the Bayes factor: A Shiny/R app
Teaching StatisticsAbstractMost researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p‐value. Null hypothesis Bayesian testing and its so‐called Bayes factor are now becoming increasingly popular. Although the Bayes
Jorge N. Tendeiro +3 more
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Sequential Bayesian Tests and the Hypothesis of independent or naive Bayes
Revista de la Facultad de Ciencias, 2018 Quite frequently diagnosis is not final with one medical test but a sequence of tests are applied. How the information given by one test is going to be combined with the information conveyed by a second test? Can we ”add up” the information of the medical
Jovadell Cruz, Luis Raúl Pericchi
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