Instead, I want to argue here that we should be preregistering every experiment do. The cost is extremely low and the benefits – both to the research process and to the credibility of our results – are substantial. Starting in the past few months, my lab has begun to preregister every study we run. You should too.
The key insights for me were:
- Different preregistrations can have different levels of detail. For some studies, you write down "we're going to run 24 participants in each condition, and exclude them if they don't finish." For others you specify the full analytic model and the plots you want to make. But there is no study for which you know nothing ahead of time.
- You can save a ton of time by having default analytic practices that don't need to be registered every time. For us these live on our lab wiki (which is private but I've put a copy here).
- It helps me get confirmation on what's ready to run. If it's registered, then I know that we're ready to collect data. I especially like the interface on AsPredicted, that asks coauthors to sign off prior to the registration going through. (This also incidentally makes some authorship assumptions explicit).