The new year is here, and many of us start off with some resolutions. Following this trend, I thought it would be fun to share some things I’ve been doing and will continue to do that mostly (with the exception of point 3) require only little effort on my side and which positively impact my sciencing and that of those around me. Continue reading 7 small things you can do for science in 2017
Meet Anne Scheel, PhD candidate at LMU Munich. She stood up and asked the author of the opinion piece on “methodological terrorism” for a statement after her keynote at the DGPS conference. Since tough questions in front of big audiences by young women are still a rare thing to encounter at conferences (and elsewhere), we were curious to know how this went down for her. And of course, we also took the opportunity to discuss the content of the piece in question. Continue reading An interview with a next generation methodological freedom fighter
The great preregistration challenge is here, so this is a perfect time to preregister your next study. After all, when do you get the chance to win money for your research? But some might wonder what this pre-thingy is…
Preregistration is a simple, and yet surprisingly novel (as far as I know), idea to ensure that researchers follow the scientific method. In other words, a preregistration means you decide before data collection what (which phenomenon, population) you want to test how (procedure, stimuli, measures, and perhaps most importantly statistics). This is the very definition of testing hypotheses, because commencing data collection should be marking a point of no return when it comes to hypotheses, variables, and statistics. The exception is exploratory work, I will go into detail later on that topic. But back to a typical experiment, the (idealized) lifecycle is illustrated below. Note the arrows going only in one direction and the red line you should definitely not cross between data collection and planning your analyses based on pre-specified hypotheses.
The topic of “New Methods” or “New Statistics” is a vocation for some, a pet subject for others, an unavoidable obstacle for yet others. And finally, it is an expression unheard of, or at least unfamiliar, to many*.
Whichever way we stand on this subject, however, what seems clear is that sooner or later we need to face it in some way or the other. And although this means that it is unavoidable, I am convinced that it is a topic that moves our field forward and carries long-term benefits.