“Small Effects: The Indispensable Foundation for a Cumulative Psychological Science”, 2021-07-02 (; backlinks; similar):
We draw on genetics research to argue that complex psychological phenomena are most likely determined by a multitude of causes and that any individual cause is likely to have only a small effect.
Building on this, we highlight the dangers of a publication culture that continues to demand large effects. First, it rewards inflated effects that are unlikely to be real and encourages practices likely to yield such effects. Second, it overlooks the small effects that are most likely to be real, hindering attempts to identify and understand the actual determinants of complex psychological phenomena.
We then explain the theoretical and practical relevance of small effects, which can have substantial consequences, especially when considered at scale and over time. Finally, we suggest ways in which scholars can harness these insights to advance research and practices in psychology (ie. leveraging the power of big data, machine learning, and crowdsourcing science; promoting rigorous preregistration, including prespecifying the smallest effect size of interest; contextualizing effects; changing cultural norms to reward accurate and meaningful effects rather than exaggerated and unreliable effects).
Only once small effects are accepted as the norm, rather than the exception, can a reliable and reproducible cumulative psychological science be built.
[See variance-components for one route forward in quantifying small effects given the daunting statistical power challenges. Götz et al appear locked into the conventional framework of directly estimating effects, when what they really need to borrow from genetics is looking at variance terms like heritability… You can’t afford to gather n in the millions when you aren’t even sure your haystack contains a needle!]