Correlation may not imply causation, but let’s just ignore that for a second. Correlations are standardized effect size metrics and as such have some quirks by design. These are benign enough when you just calculate a single correlation coefficient and look at it, but things can get really messy onc| The 100% CI
In some fields, researchers who end up with time series of two variables of interest (X and Y) like to analyze (reciprocal) lagged effects between them. Does X affect Y at a later point in time, and does Y affect X at a later point in time? These questions are usually addressed with some sort of pan| The 100% CI
Mediation analysis has gotten a lot of flak, including classic titles such as “Yes, but what’s the mechanism? (Don’t expect an easy answer)” (Bullock et al., 2010), “What mediation analysis can (not) do” (Fiedler et al., 2011), “Indirect effect ex machina” (The 100% CI, 2019), “In psychology everyth| The 100% CI
The longer I have been in psychological research, the more I wonder about why we do things the way we do. Why do we sometimes get all fancy about some aspects of statistical modeling (e.g., imputation of missing values on a high performance cluster that takes days) and sometimes stay rather unsophis| The 100% CI
Guest post by Taym Alsalti. If you want a citable version, see this preprint with Jamie Cummins & Ruben Arslan.…| The 100% CI
For any central statistical analysis that you report in your manuscript, it should be absolutely clear for readers why the analysis is being conducted in the first place – that is, the analysis goal should be transparently communicated. A helpful concept here is the so-called theoretical estimand, t| The 100% CI
Reviewer notes are a new short format with brief explanations of basic ideas that might come in handy during (for example) the peer-review process. They are a great way to keep Julia from writing 10,000-word-posts,but make her write ten 1,000-word-posts instead and also a great| The 100% CI
The 100% CI unravels serial cases of mysterious research misconduct by a single villain: Rogue RA| The 100% CI
In The Anxious Generation, Jon Haidt argues that social media is driving a mental health crisis among teens. It's a compelling thesis, widely discussed in the media, mostly accepted by my students and even by me—for a while. I felt I owed this book a read given that this is a topic many of my studen| The 100% CI
A shibboleth is a custom, such as a choice of phrasing, that distinguishes one group of people from another. The…| The 100% CI
A wise man – I’m quite sure it was Brian Wansink – once pointed out that it is impossible to both read and write a lot. So, maybe reading a post about how to write just steals time from the more urgent task of writing more. Then again, maybe it wouldn’t have hurt Wansink if he had spent more time re| The 100% CI
Update 2022: There is now a manuscript that discusses the topic of this blog post in more depth, see preprint here. While reviewing papers, I’ve noticed some boilerplate that keeps creeping up in the “Limitations” sections of studies using cross-sectional, observational designs: “Of course, we| The 100% CI
Summer in Berlin – the perfect time and place to explore the city, take a walk in the Görli, go skinny dipping in the Spree, attend an overcrowded, overheated conference symposium on cross-lagged panel models (#noAircon). So that’s what I did three weeks ago at the European Conference on Personality| The 100% CI
TL;DR: Tell your students about the potential outcomes framework. It will have (heterogeneous) causal effects on their understanding of causality (mediated through unknown pathways), I promise. It’s probably fair to say that many psychological researchers are somewhat confused about causal infere| The 100% CI
I don’t like getting into fights and sometimes I am concerned this keeps me from becoming a proper methods/stats person. Getting into fights about one or multiple (or all) of the following just seems to be part of the job: p values (the canonical point of contention) Bayes factors structur| The 100% CI
Content warning: half-assed philosophy of science Part I: Causal Inference I am not very keen to join the stats wars, but if I had to join, I would rally under the banner of House Cause. That is the one framework I’d champion in a (randomised controlled) trial-by-combat if necessary: Autho| The 100% CI
It is the curse of transparency that the more you disclose about your research process, the more there is to criticize. If you write a preregistration, every minor change of protocol can be uncovered and held against you. If you share your analysis code, every minor typo can be detected and interpre| The 100% CI
