Overcoming Challenges in Preregistration to Improve Statistical Inferences in Clinical Science

Preregistration of hypotheses and analysis plans on a public, time-stamped registry (e.g., Open Science Framework; OSF) before observing research outcomes promotes transparency and distinguishes planned from unplanned analyses, thereby guarding against selective reporting, improving validity of inferences for planned analyses, and enabling calibration of confidence for unplanned analyses (Nosek et al., 2018; Nosek et al., 2019). Further, preregistration can benefit individual researchers by enabling credit for planned analyses (e.g., in-principle acceptance of Registered Reports, even for null results), signaling rigor (improving publishability), revealing design flaws early, aiding recall of study details and plans, and improving communication with collaborators (Logg & Dorison, 2021; Simmons et al., 2021; Wagenmakers & Dutilh, 2016). Clinical psychologists may be familiar with registering clinical trial procedures (e.g., eligibility criteria, conditions, outcomes) on websites such as ClincalTrials.gov; however, procedures are registered for only a fraction of trials (Nutu et al., 2019), and where registration is required (e.g., by U.S. law), detailed analysis plans (beyond listing outcomes) are not yet required (Cybulski et al., 2016; Nosek et al., 2018). Preregistering detailed hypotheses and analysis plans can be difficult (Nosek et al., 2019); the present article addresses calls for more training (Berenbaum et al., 2021) by presenting strategies for overcoming challenges in clinical science (for resources on creating a preregistration and applying key strategies, see Table S1 at https://doi.org/kbv8).