2016
DOI: 10.31234/osf.io/ph6sw
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How to become a Bayesian in eight easy steps: An annotated reading list

Abstract: In this guide, we present a reading list to serve as a concise introduction to Bayesian data analysis. The introduction is geared toward reviewers, editors, and interested researchers who are new to Bayesian statistics. We provide commentary for eight recommended sources, which together cover the theoretical and practical cornerstones of Bayesian statistics in psychology and related sciences.

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Cited by 17 publications
(17 citation statements)
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References 22 publications
(28 reference statements)
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“…We interpret these values through the 95% highest probability mass ("confidence interval" in the Bayesian perspective). For an accessible introduction to Bayesian data analysis and interpretation, see Kruschke & Liddell, 2017, Etz, Gronau, Dablander, Edelsbrunner & Baribault, 2016. We observed a main effect of RWA on ratings:…”
Section: Bayesian Resultsmentioning
confidence: 88%
“…We interpret these values through the 95% highest probability mass ("confidence interval" in the Bayesian perspective). For an accessible introduction to Bayesian data analysis and interpretation, see Kruschke & Liddell, 2017, Etz, Gronau, Dablander, Edelsbrunner & Baribault, 2016. We observed a main effect of RWA on ratings:…”
Section: Bayesian Resultsmentioning
confidence: 88%
“…Importantly, by performing Bayesian factor analyses, we were not only able to quantify the amount of evidence in favour of the effect under scrutiny, but we could also quantify the evidence in favour of the null hypothesis, something that cannot be achieved by means of NHST (Dienes, 2011;Etz et al, 2017;Rouder et al, 2009;Wagenmakers, 2007). Although the evidence in favour of a bias was very strong in the cued conditions, the evidence in favour of no effect in the no cue condition seemed weaker.…”
Section: Discussionmentioning
confidence: 99%
“…Choosing a narrower distribution (i.e., a lower value of r), would result in a high level of similarity between H 1 and H 0 , making the tests uninformative. Conversely, choosing an unreasonably wide distribution would result in the BF favouring the null too heavily, by placing too much weight on extreme effect size values (Etz et al, 2017;Rouder et al, 2009;Wagenmakers et al, 2017). In addition to calculating the BF, robustness checks and sequential analyses (combined with a robustness analysis) of the BF were carried out and visualized in plots.…”
Section: Statistical Proceduresmentioning
confidence: 99%
“…Sense anar tan lluny, moltes de les revistes tradicionals en Psico logia, com Psychological Science (APS), estan ampliant l'espai que dediquen a descriure els mètodes i els procediments, de manera que aquests puguen ser coneguts amb detall, al mateix temps que fomenten noves perspectives esta dístiques que eviten −o almenys compensen en certa mesura− els problemes associats als valors p i, en general, als tests de significació que es basen en la hipòtesi nul·la. Entre aquestes noves perspectives està l'ús adequat de l'anàlisi de potència, l'estudi de les grandàries de l'efecte amb intervals de confiança associats o, últimament, l'estadística bayesiana (Cumming, 2014;Etz, Gronau, Dablander, Edelsbrunner i Baribault, 2016;Wagenmakers, 2007).…”
Section: A) Polítiques Editorials Diferentsunclassified