The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
On the use of Non-Local Prior Densities in Bayesian Hypothesis Tests
Open accessAbstract
Summary: We examine philosophical problems and sampling deficiencies that are associated with current Bayesian hypothesis testing methodology, paying particular attention to objective Bayes methodology. Because the prior densities that are used to define alternative hypotheses in many Bayesian tests assign non-negligible probability to regions of the parameter space that are consistent with null hypotheses, resulting tests provide exponential accumulation of evidence in favour of true alternative hypotheses, but only sublinear accumulation of evidence in favour of true null hypotheses. Thus, it is often impossible for such tests to provide strong evidence in favour of a true null hypothesis, even when moderately large sample sizes have been obtained. We review asymptotic convergence rates of Bayes factors in testing precise null hypotheses and propose two new classes of prior densities that ameliorate the imbalance in convergence rates that is inherited by most Bayesian tests. Using members of these classes, we obtain analytic expressions for Bayes factors in linear models and derive approximations to Bayes factors in large sample settings.
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The Intrinsic Bayes Factor for Model Selection and Prediction
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Cited by
Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
Simpson, D., Rue, H., Riebler, A., Martins, T. G., & Sørbye, S. H. (2017) · Statistical Science · doi:10.1214/16-sts576 · Cited by 1,085
A solution to minimum sample size for regressions
Jenkins, D. G., & Quintana-Ascencio, P. F. (2020) · PLOS ONE · doi:10.1371/journal.pone.0229345 · Cited by 665
“Bayesian approaches analogous to power exist [44,45] but have not yet been widely applied to this problem.”
BackgroundModel Averaging and Its Use in Economics
Steel, M. F. J. (2020) · Journal of Economic Literature · doi:10.1257/jel.20191385 · Cited by 321
The philosophy of Bayes factors and the quantification of statistical evidence
Morey, R. D., Romeijn, J.-W., & Rouder, J. N. (2016) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2015.11.001 · Cited by 313
A tutorial on Bayes Factor Design Analysis using an informed prior
Stefan, A. M., Gronau, Q. F., Schönbrodt, F. D., & Wagenmakers, E.-J. (2019) · Behavior Research Methods · doi:10.3758/s13428-018-01189-8 · Cited by 284
Metadata
- Authors
- Johnson, V. E., & Rossell, D.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-01-28
- Volume
- 72
- Issue
- 2
- Pages
- 143-170
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W2053675401
- Cited by
- 279
- References
- 35
- FWCI
- 8.35
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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