Prof. Dr. Felix Schönbrodt
If we want to shift from a closed science to an open science, there has to be change at several levels. In this process, it’s easy to push the responsibility (and the power) for reform onto “the system”: “If only 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 …
Yesterday, we had the first meeting of our department’s Open Science Committee. I am happy that the committee has 20 members, representing every research unit of the department, and all groups from PhD students to full professors. In the meeting, Continue Reading …
The Reproducibility Project: Psychology was published last week, and it was another blow to the overall credibility of the current research system’s output. Some interpretations of the results were in a “Hey, it’s all fine; nothing to see here; let’s 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 …
Large-scale replication projects of the last years (e.g., ManyLabs I, II, and III, Reproducibility Project: Psychology) showed that the “replication crisis” in psychology is more than just hot air: According to recent estimates, ~60% of current psychological research is [tooltip 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 …
[This is a guest post by Eric-Jan Wagenmakers and Quentin Gronau introducing the RGraphCompendium. Click here to see the full compendium!] Every data analyst knows that a good graph is worth a thousand words, and perhaps a hundred tables. But Continue Reading …
A Bayes factor (BF) is a statistical index that quantifies the evidence for a hypothesis, compared to an alternative hypothesis (for introductions to Bayes factors, see here, here or here). Although the BF is a continuous measure of evidence, humans Continue Reading …
[Update 2015/1/14: I consolidate feedback from Twitter, comments, email, and real life into the main text (StackExchange-style), so that we get a good and improving answer. Thanks to @TonyLFreitas, @PhDefunct, @bahniks, @JoeHilgard, @_r_c_a, @richardmorey, @R__INDEX, the commenters at the end of Continue Reading …