Alexander Etz: Understanding Bayes: How to become a Bayesian in eight easy steps

Alex Etz just wrote a really elegant blog post about his recent paper with Beth Baribault, Peter Edelsbrunner (@peter1328), Fabian Dablander (@fdabl), and Quentin Gronau in the special edition on Bayesian statistics for Psychonomic Bulletin and Review. In their paper they propose 8 papers that are worth reading to get into Bayesian statistics, giving a nice review / rating of these papers, as well as some others (that they still recommend, but maybe not as a crash course in Bayesian stats, but for those of us who want to learn more). If you’ve ever caught yourself thinking, I’d like to know more about Bayesian stats, but I don’t know where to start, then this paper is *literally* for you (and, well, for me, because I’ve been thinking this for too long…).

There was also recently a nice post by Wayne Folta about two packages in R that make Bayesian (regression) statistics a bit easier. Get it, Bayesians!

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Colin Phillips: How to create a top journal by accepting (almost) everything

Colin Phillips has written a really interesting, and well thought out blog post about his experience as an editor of a special topic at Frontiers in Psychology (my most recent article was published in a different special topic (Models of Reference) in Frontiers – Talker-Specific Generalization of Pragmatic Inferences based on Under- and Over-Informative Prenominal Adjective Use). He found that while the model isn’t perfect, that it can be an improvement on the current model for publishing, discussing topics such as impact factor, time-to-publish, selectivity, etc. It’s a great read! Check it out here.