When studies examine true effects, they generate right-skewed p-curves, distributions of statistically significant results with more low (.01 s) than high (.04 s) p values. What else can cause a right-skewed p-curve? First, we consider the …
Vul, Harris, Winkielman, and Pashler (2009), (this issue) argue that correlations in many cognitive neuroscience studies are grossly inflated due to a widespread tendency to use nonindependent analyses. In this article, I argue that Vul et al.'s …
Publication bias leads consumers of research to observe a selected sample of statistical estimates calculated by producers of research. We calculate critical values for statistical significance that could help to adjust after the fact for the …
Publication bias and questionable research practices in primary research can lead to badly overestimated effects in meta-analysis. Methodologists have proposed a variety of statistical approaches to correct for such overestimation. However, it is not …
The concept of validity has suffered because the term has been used to refer to 2 incompatible concerns: the degree of support for specified interpretations of test scores (i.e., intended score meaning) and the degree of support for specified …
Significance testing based on p-values is standard in psychological research and teaching. Typically, research articles and textbooks present and use p as a measure of statistical evidence against the null hypothesis (the Fisherian interpretation), …
The practice of hypothesizing after results are known (HARKing) has been identified as a potential threat to the credibility of research results. We conducted simulations using input values based on comprehensive meta-analyses and reviews in applied …
Statistical rituals largely eliminate statistical thinking in the social sciences. Rituals are indispensable for identification with social groups, but they should be the subject rather than the procedure of science. What I call the “null ritual” …
Criticisms of null-hypothesis significance tests (NHSTs) are reviewed. Used as formal, two-valued decision procedures, they often generate misleading conclusions. However, critics who argue that NHSTs are totally meaningless because the null …
Because scientists tend to report only studies (publication bias) or analyses (p-hacking) that “work,” readers must ask, “Are these effects true, or do they merely reflect selective reporting?” We introduce p-curve as a way to answer this question. …