1999
DOI: 10.2307/2670175
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Default Bayes Factors for Nonnested Hypothesis Testing

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Cited by 64 publications
(67 citation statements)
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“…In order to increase the robustness of Bayesian hypothesis testing to the vagueness of the prior, several procedures have been proposed, including the local Bayes factor (Smith & Spiegelhalter, 1980), the intrinsic Bayes factor (Berger & Mortera, 1999;Berger & Pericchi, 1996), the fractional Bayes factor (O'Hagan, 1995), and the partial Bayes factor (O'Hagan, 1995; for a summary see Gill, 2002, chap. 7).…”
Section: Challenges For Bayesian Hypothesis Testingmentioning
confidence: 99%
“…In order to increase the robustness of Bayesian hypothesis testing to the vagueness of the prior, several procedures have been proposed, including the local Bayes factor (Smith & Spiegelhalter, 1980), the intrinsic Bayes factor (Berger & Mortera, 1999;Berger & Pericchi, 1996), the fractional Bayes factor (O'Hagan, 1995), and the partial Bayes factor (O'Hagan, 1995; for a summary see Gill, 2002, chap. 7).…”
Section: Challenges For Bayesian Hypothesis Testingmentioning
confidence: 99%
“…This fact does not a surprising result. Berger and Mortera (1999) studied that the FBF gives the considerable bias in the direction of one of the hypotheses in non-symmetric situations. And so the FBF can not be used for the hypotheses testing in the case of non-symmetric circumstances.…”
Section: Numerical Studiesmentioning
confidence: 99%
“…Finally, the experiment would also stop on October 1st, 2013. Even though we preregistered a sampling plan, note that the sampling plan is irrelevant for Bayesian inference (e.g., Berger & Mortera, 1999;Berger & Wolpert, 1988;Rouder, 2014); as summarized by Edwards et al (1963, p. 193): "the rules governing when data collection stops are irrelevant to data interpretation. It is entirely appropriate to collect data until a point has been proven or disproven, or until the data collector runs out of time, money, or patience".…”
Section: Sampling Planmentioning
confidence: 99%
“…Specifically, we planned to use default Bayes factors for unpaired, one-sided t-tests as outlined in Rouder et al (2009) and Wetzels et al (2009), that is, a folded Cauchy distribution with a mode at 0 and a scale of 1 (see also Jeffreys, 1961, and. We would monitor the Bayes factor as the data come in, and report the results as a function of the number of participants, using sequential analysis plot (see Figure 2 in Wagenmakers et al, 2012; see also Berger & Mortera, 1999, Table 1). This study was planned in 2013, and since then Morey and Rouder (2015) have advocated a default Cauchy scale of r = 0.707.…”
Section: Statistical Analysesmentioning
confidence: 99%
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