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Every once in a while I find myself daydreaming about various ways to up my game in the kitchen and, recently, that dream morphed into an obsession over trying to bake seriously good bread in a home kitchen. But not just any bread: sourdough bread. As strange as it may seem, my bread obsession was triggered by another obsession, namely, knives and knife sharpening. Until recently, our kitchen knives were not all that sharp—I have had them ever since I was a graduate student, which dates their purchase to sometime during the Paleozoic Era.

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It is not uncommon to encounter practitioners who scribble down a parametric regression model and then proceed as if their model had generated the data.1 No model selection exercise is attempted, model uncertainty is ignored, and statements are made about the underlying process that generated the data based solely on the model they scribbled down. That is, they proceed as if their ad hoc model is the one true model that faithfully mimics the unknown data generating process (DGP) and therefore could plausibly have generated the data.

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Knowledge transfer and the dissemination of research are vital components of the academic mission, yet sometimes these are afforded no more than an afterthought. I strive to impress upon my students and colleagues the often overlooked importance of replicability, automated backup procedures, and version control. But dissemination of work via academic conferences, being a visible member of the international academic community, and in general “marketing” our research to others often gets short shrift.

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Yesterday I was discussing workflow with a PhD student who I recently started supervising and I encouraged her to get up to speed with GitHub, which she did. I also discussed how I use GitHub when working with co-authors on R packages by adding them as “contributors” to a public GitHub repository (the default repository type on GitHub). I further suggested that this could be an ideal way for me to guide her through the process of writing her dissertation since, for one, tracking changes is trivial and relieves me of having to re-read chapters multiple times (she is writing her dissertation using R Markdown and bookdown, naturally).

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The R package blogdown “is an effort to integrate R Markdown with static website generators” according to its creator, Yihui Xie. He writes “Besides the advantage in website structures, another highlight of blogdown is that it inherited bookdown’s Markdown extensions (based on Pandoc’s Markdown), which means you can easily write technical content on your website, including everything that Pandoc supports (e.g., headings, lists, footnotes, tables, figures, citations, \(\LaTeX\) math, and quotes, etc) and bookdown’s extensions (e.

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