Preprint: A Bayesian Multiverse Analysis of Many Labs 4

Below is a summary of a preprint featuring an extensive reanalysis of the results Many Labs 4 project (current preprint). ML4 attempted to replicate the mortality salience effect. Following the publication of the preprint a heated debate broke out about data inclusion criteria. In an attempt of conciliation we decided to reanalyze the data using all proposed data inclusion criteria…

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On the Beauty of Publishing an Ugly Registered Report

I was exhausted and expecting my newborn to wake up any moment, but I wanted to look at the data. I had stopped data collection a month prior, and wasn’t due back at work for weeks, so it could have waited, but my academic brain was beginning to stir after what seemed like eons of pregnancy leave. Sneaking a peek…

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Preprint: A Bayesian Reanalysis of the Effects of Hydroxychloroquine and Azithromycin on Viral Carriage in Patients with COVID-19 (Reply to Gautret et al. 2020)

Below is a summary of a preprint that features a Bayesian reanalysis of the famous/infamous Gautret et al. data. What I like about this preprint is (a) the multiverse analysis; (b) the Bayesian conclusions — they are so easy to obtain with JASP, and provide much more information then just “p<.05” or “p>.05”; but what I like most of all…

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Corona and the Statistics Wars

As the corona-crisis engulfs the world, politicians left and right are accused of “politicizing” the pandemic. In order to follow suit I will try to weaponize the pandemic to argue in favor of Bayesian inference over frequentist inference. In recent months it has become clear that the corona pandemic is not just fought by doctors, nurses, and entire populations as…

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Preprint: Default Bayes Factors for Testing the (In)equality of Several Population Variances

This post summarizes Dablander, F.⭑, van den Berg, D.⭑, Ly, A., Wagenmakers, E.-J. (2020). Default Bayes Factors for Testing the (In)equality of Several Population Variances. Preprint available on ArXiv:                                     https://arxiv.org/abs/2003.06278. Abstract “Testing the (in)equality of variances is an important problem in many…

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David Spiegelhalter’s Gullible Skeptic, and a Bayesian “Hard-Nosed Skeptic” Reanalysis of the ANDROMEDA-SHOCK Trial

In a recent blog post, Bayesian icon David Spiegelhalter proposes a new analysis of the results from the ANDROMEDA-SHOCK randomized clinical trial. This trial was published in JAMA under the informative title “Effect of a Resuscitation Strategy Targeting Peripheral Perfusion Status vs Serum Lactate Levels on 28-Day Mortality Among Patients With Septic Shock”. In JAMA, the authors summarize their findings…

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Misconception: The Relative Belief Ratio Equals the Marginal Likelihood

The Misconception The relative belief ratio (e.g., Evans 2015, Horwich 1982/2016) equals the marginal likelihood. The Correction The relative belief ratio is proportional to the marginal likelihood. Dividing two marginal likelihoods (i.e., computing a Bayes factor) cancels the constant of proportionality, such that the Bayes factor equals the ratio of two complementary relative belief ratios (Evans 2015, p.109, proposition 4.3.1).…

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