Prof. Dr. Felix Schönbrodt
by Angelika Stefan & Felix Schönbrodt Almost all researchers have experienced the tingling feeling of suspense that arises right before they take a look at long-awaited data: Will they support their favored hypothesis? Will they yield interesting or even groundbreaking Continue Reading …
tl;dr: Publication bias and p-hacking can dramatically inflate effect size estimates in meta-analyses. Many methods have been proposed to correct for such bias and to estimate the underlying true effect. In a large simulation study, we studied which methods do Continue Reading …
Recently, Matt Motyl et al. (2017) posted a pre-print paper in which they contrasted the evidential value of several journals in two time periods (2003-2004 vs. 2013-2014). The paper sparked a lot of discussion in Facebook groups [1][2], blog posts Continue Reading …
by Angelika Stefan & Felix Schönbrodt This is the second part of “Two meanings of priors”. The first part explained a first meaning – “priors as subjective probabilities of models”. While the first meaning of priors refers to a global Continue Reading …
by Angelika Stefan & Felix Schönbrodt When reading about Bayesian statistics, you regularly come across terms like “objective priors“, “prior odds”, “prior distribution”, and “normal prior”. However, it may not be intuitively clear that the meaning of “prior” differs in Continue Reading …
Democratizing p-hacking: Leveling the playing field by teaching p-hacking to students and early career researchers. Continue Reading …
tl;dr: Optional stopping does not bias parameter estimates from a frequentist point of view if all studies are reported (i.e., no publication bias exists) and effect sizes are appropriately meta-analytically weighted. Several recent discussions on the Psychological Methods Facebook group Continue Reading …
If the p-value is < .05, then the probability of falsely rejecting the null hypothesis is <5%, right? That means, a maximum of 5% of all significant results is a false-positive (that’s what we control with the α rate). Well, Continue Reading …
I am pleased to announce that Marco Perugini and I have received the 2015 Best Paper Award from the Association of Research in Personality (ARP) for our paper: Schönbrodt, F. D., & Perugini, M. (2013). At what sample size do Continue Reading …
There are at least three traditions in statistics which work with a kind of likelihood ratios (LRs): the “Bayes factor camp”, the “AIC camp”, and the “likehood camp”. In my experience, unfortunately most people do not have an intuitive understanding Continue Reading …