When I first started graduate school, my advisor Dave Kenny handed me a book he was writing on dyadic data analysis and said “Here, go try and replicate all of the analyses in this book and tell me if you find mistakes.” I was terrified. What if he realized I didn’t actually know anything yet? Did I oversell myself during grad interview weekend? Several months later I managed to work my way through the book. Now I look back on that experience and it’s clear to me that this exercise wasn’t a test for me it was a test for Dave and his co-authors—they wanted to make sure that the book was transparent and clear, and that anyone in graduate school (including first years!) could follow it.
Fast forward a decade and a half later, and I am still using that book to teach dyadic analysis to others. The lesson from that exercise still rings true today when I teach: You aren't doing good job at being a clear communicator if others who read your work can't follow your guidelines. One of the most enjoyable parts of my job is making advanced statistical procedures and methodologies approachable to scientists; the best teachers are those who can successfully remove the intimidation factor that many students (and faculty and post docs) experience when they first encounter a new methodological technique they aren’t familiar with. Over the years I have taught many workshops, and I have also published “how to” papers that try to make statistics approachable and understandable. I have created several webinars that guide people in executing steps needed for analyzing data, all of which are available to the public.
As a scientist, I think that transparency and clarity are critical. To help achieve these goals, I have created video protocol for my lab studies, which I think can go a long way in making the methodology of a study come to life. I am also very open with my own data and syntax, and I urge others to be so as well. Willingness to share data, materials, and statistical code is important for replication, but I’ve also found that it goes a long way in helping others learn statistical procedures.
As science-publishing member at large, I would hope to bring my goals of transparency and clarity to the publication process. My current experience as senior editor at PSPB and statistics advisor at Psychological Science have taught me just how important clarity and transparency are when communicating our research.