I wrote an invited review for Developmental Medicine & Child Neurology about “Practical tools and strategies for researchers to increase replicability”.

Problems with replicability have been widely discussed over the last years, especially in psychology. By now, a lot of promising solutions have been proposed, but my sense is that researchers are sometimes a bit overwhelmed by all the possibilities.

My goal in this review was to make a list of some of the current recommendations that can be easily implemented. Not every solutions is always feasible for every project, so my advice is: copy best practices from other fields, see what works on a case-by-case basis, and improve your research step by step.

The preprint can be found here: https://psyarxiv.com/emyux.

Our new meta-meta-analysis on intelligence research is now online as a preprint at https://psyarxiv.com/ytsvw.

We analyzed 131 meta-analyses in intelligence research to investigate effect sizes, power, and patterns of bias. We find a typical effect of r = .26 and a median sample size of 60.

The median power seems low (see figure below), and we find evidence for small study effects, possibly indicating overestimated effects. We don’t find evidence for a US effect, decline or early-extremes effect, or citation bias.

Comments are very welcome and can be posted on the PubPeer page https://pubpeer.com/publications/9F209A983618EFF9EBED07FDC7A7AC.