Preprint: BFpack — Flexible Bayes Factor Testing of Scientific Theories in R

This post is a synopsis of Mulder, J., Gu, X., Olsson-Collentine, A., Tomarken, A., Böing-Messing, F., Hoijtink, H., Meijerink, M., Williams, D. R., Menke, J., Fox, J.-P., Rosseel, Y., Wagenmakers, E.-J., & van Lissa, C. (2019). BFpack: Flexible Bayes factor testing of scientific theories in R. Preprint available at https://arxiv.org/pdf/1911.07728.pdf Abstract “There has been a tremendous methodological development of Bayes…

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Crowdsourcing Hypothesis Tests: The Bayesian Perspective

This post is a synopsis of the Bayesian work featured in Landy et al. (in press). Crowdsourcing hypothesis tests: Making transparent how design choices shape research results. Psychological Bulletin. Preprint available at https://osf.io/fgepx/; the 325-page supplement is available at https://osf.io/jm9zh/; the Bayesian analyses can be found on pp. 238-295. Abstract “To what extent are research results influenced by subjective decisions…

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Preprint: Practical Challenges and Methodological Flexibility in Prior Elicitation

This post is an extended synopsis of Stefan, A. M., Evans, N. J., & Wagenmakers, E.-J. (2019). Practical challenges and methodological flexibility in prior elicitation. Manuscript submitted for publication. Preprint available on PsyArXiv: https://psyarxiv.com/d42xb/       Abstract It is a well-known fact that Bayesian analyses require the specification of a prior distribution, and that different priors can lead to…

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A Breakdown of “Preregistration is Redundant, at Best”

In this sentence-by-sentence breakdown of the paper “Preregistration is Redundant, at Best”, I argue that preregistration is a pragmatic tool to combat biases that invalidate statistical inference. In a perfect world, strong theory sufficiently constrains the analysis process, and/or Bayesian robots can update beliefs based on fully reported data. In the real world, however, even astrophysicists require a firewall between…

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How to Evaluate a Subjective Prior Objectively

The Misconception Gelman and Hennig (2017, p. 989) argue that subjective priors cannot be evaluated by means of the data: “However, priors in the subjectivist Bayesian conception are not open to falsification (…), because by definition they must be fixed before observation. Adjusting the prior after having observed the data to be analysed violates coherence. The Bayesian system as derived…

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Did Alan Turing Invent the Bayes factor?

The otherwise excellent article by Consonni et al. (2018), discussed last week, makes the following claim: “…the initial use of the BF can be attributed both to Jeffreys and Turing who introduced it independently around the same time (Kass & Raftery, 1995)” (Consonni et al., 2018, p. 638)                   This claim recently…

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“Prior Distributions for Objective Bayesian Analysis”

The purpose of this blog post is to call attention to the paper “Prior Distributions for Objective Bayesian Analysis”, authored by Guido Consonni, Dimitris Fouskakis, Brunero Liseo, and Ioannis Ntzoufras (NB: Ioannis is a member of the JASP advisory board!). The paper –published in the journal “Bayesian Analysis”— provides a comprehensive overview of objective Bayesian analysis, with an emphasis on…

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Book Review of “Bayesian Probability for Babies”

“Bayesian Probability for Babies” is a book that explains Bayes’ rule through a simple story about cookies. I battle-tested the book on my two-year old son Theo (admittedly no longer a baby), and he seemed somewhat intrigued by the idea of candy-covered cookies, although the more subtle points of the story must have eluded him. Theo gives the book three…

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