This article reports on an adversarial (but friendly) collaboration examining the issues that lie at the intersection of confidentiality and open-data practices. We describe the process we followed to share our data for a speed-dating article we …
In 2010–2012, a few largely coincidental events led experimental psychologists to realize that their approach to collecting, analyzing, and reporting data made it too easy to publish false-positive findings. This sparked a period of methodological …
The past several years have been a time for soul searching in psychology, as we have gradually come to grips with the reality that some of our cherished findings are less robust than we had assumed. Nevertheless, the replication crisis highlights the …
Most discussions of rigor and replication focus on empirical practices (methods used to collect and analyze data). Typically overlooked is the role of conceptual practices: the methods scientists use to arrive at and articulate research hypotheses in …
Publication bias is the tendency on the parts of investigators, reviewers, and editors to submit or accept manuscripts for publication based on the direction or strength of the study findings. Much of what has been learned about publication bias …
For any given research area, one cannot tell how many studies have been conducted but never reported. The extreme view of the "file drawer problem" is that journals are filled with the 5% of the studies that show Type I errors, while the file drawers …
Because physical theories typically predict numerical values, an improvement in experimental precision reduces the tolerance range and hence increases corroborability. In most psychological research, improved power of a statistical design leads to a …
Short and rapid publication of research findings has many advantages. However, there is another side of the coin that needs careful consideration. We argue that the most dangerous aspect of a shift toward “bite-size” publishing is the relationship …
We discuss three arguments voiced by scientists who view the current outpouring of concern about replicability as overblown. The first idea is that the adoption of a low alpha level (e.g., 5%) puts reasonable bounds on the rate at which errors can …