Preregistration Distinguishes Between Exploratory and Confirmatory Research? Previous justifications for preregistration have focused on the distinction between “exploratory” and “confirmatory” research. However, as I discuss in this recent presentation, this distinction faces unresolved questions. For example, the distinction does not appear to have a formal definition in either statistical theory or the philosophy of science.

A conference called “The promises and pitfalls of preregistration” was hosted by the Royal Society in London from 4th-5th March 2024. Here, I discuss the presentations by Chris Donkin and Stephan Lewandowsky, both of which consider some of the potential “pitfalls” of preregistration.

In an article published last week in Synthese, philosopher of science Pekka Syrjänen asked “does a theory become better confirmed if it fits data that was not used in its construction versus if it was specifically designed to fit the data?” The first approach is called prediction, and the second approach is called accommodation . The debate over the epistemic advantages of prediction and accommodation has been bubbling away for

The Costs of HARKing: Does it Matter if Researchers Engage in Undisclosed Hypothesizing After the Results are Known? While no-one’s looking, a Texas sharpshooter fires his gun at a barn wall, walks up to his bullet holes, and paints targets around them. When his friends arrive, he points at the targets and claims he’s a good shot.

In this new paper (Rubin, 2021), I consider when researchers should adjust their alpha level (significance threshold) during multiple testing and multiple comparisons. I consider three types of multiple testing (disjunction, conjunction, and individual), and I argue that an alpha adjustment is only required for one of these three types.