Curiouser and Curiouser: Down the Rabbit Hole with the One-Sided P-value

  WARNING: This is a Bayesian perspective on a frequentist procedure. Consequently, hard-core frequentists may protest and argue that, for the goals that they pursue, everything makes perfect sense. Bayesians will remain befuddled. Also, I’d like to thank Richard Morey for insightful, critical, and constructive comments. In an unlikely alliance, Deborah Mayo and Richard Morey (henceforth: M&M) recently produced an…

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A Comprehensive Overview of Statistical Methods to Quantify Evidence in Favor of a Point Null Hypothesis: Alternatives to the Bayes Factor

An often voiced concern about p-value null hypothesis testing is that p-values cannot be used to quantify evidence in favor of the point null hypothesis. This is particularly worrisome if you conduct a replication study, if you perform an assumption check, if you hope to show empirical support for a theory that posits an invariance, or if you wish to…

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Throwing out the Hypothesis-Testing Baby with the Statistically-Significant Bathwater

Over the last couple of weeks several researchers campaigned for a new movement of statistical reform: To retire statistical significance. Recently, the pamphlet of the movement was published in form of a comment in Nature, and the authors, Valentin Amrhein, Sander Greenland, and Blake McShane, were supported by over 800 signatories. Retire Statistical Significance When reading the comment we agreed…

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Preprint: A Conceptual Introduction to Bayesian Model Averaging

  Preprint: doi:10.31234/osf.io/wgb64 Abstract “Many statistical scenarios initially involve several candidate models that describe the data-generating process. Analysis often proceeds by first selecting the best model according to some criterion, and then learning about the parameters of this selected model. Crucially however, in this approach the parameter estimates are conditioned on the selected model, and any uncertainty about the model…

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Jeffreys’s Oven

Recently I was involved in an Email correspondence where someone claimed that Bayes factors always involve a point null hypothesis, and that the point null is never true — hence, Bayes factors are useless, QED. Previous posts on this blog here and here discussed the scientific relevance (or even inevitability?) of the point null hypothesis, but the deeper problem with…

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Preprint: Five Bayesian Intuitions for the Stopping Rule Principle

Preprint: https://psyarxiv.com/5ntkd Abstract “Is it statistically appropriate to monitor evidence for or against a hypothesis as the data accumulate, and stop whenever this evidence is deemed sufficiently compelling? Researchers raised in the tradition of frequentist inference may intuit that such a practice will bias the results and may even lead to “sampling to a foregone conclusion”. In contrast, the Bayesian…

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Book Review: “The Seven Deadly Sins of Psychology”

This book review is a translated and slightly adjusted version of one that is currently in press for “De Psycholoog”. The review was inspired by the recent Dutch translation De 7 Doodzonden van de Psychologie (see references below). In his inaugural address on September 11th 2001, Diederik Stapel made a bold claim about the prestige and accomplishments of the field…

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Addressing Elizabeth Loftus’ Lament: When Peeking at Data is Guilt-Free

Elizabeth Loftus is one of the world’s most influential psychologists and I have the greatest respect for her and her work. Several years ago we attended the same party and I still recall her charisma and good sense of humor. Also, Elizabeth Loftus studied mathematical psychology in Stanford, and that basically makes us academic family. But…just as Stanford math psych…

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