Foundation of Statistics & Methodology

Constructs, operationalisations, mediators, and why behavior change techniques cannot change behavior

In health psychology, there exists a lack of conceptual clarity regarding a number of terms that are at the core of psychological science. True, this problem exists in psychology in general, but the terms Behavior Change Technique (from the BCT taxonomy approach) and Method for Behavior Change (from the Intervention Mapping approach) have exacerbated matters within behavior change science. In this post, I will discuss this in more detail, based on a recent Twitter discussion that erupted around whether a psychological variable targeted by a behavior change technique is a mediator or not:

Why one randomization does not a successful experiment make

Based on a PsyArXiv preprint with the admittedly slightly provocative title “Why most experiments in psychology failed: sample sizes required for randomization to generate equivalent groups as a partial solution to the replication crisis” a modest debate erupted on Facebook (see here; you need to be in the PsychMAP group to access the link, though) and Twitter (see here, here, and here) regarding randomization. John Myles White was nice enough to produce a blog post with an example of why Covariate-Based Diagnostics for Randomized Experiments are Often Misleading (check out his blog; he has other nice entries, e.

On the obsession with being normal

In statistics, one of the first distributions that one learns about is usually the normal distribution. Not only because it’s pretty, also because it’s ubiquitous. In addition, the normal distribution is often the reference that is used when discussion other distributions: right skewed is skewed to the right compared to the normal distribution; when looking at kurtosis, a leptokurtic distribution is relatively spiky compared to the normal distribution: and unimodality is considered the norm, too.

Why one-sided tests in psychology are practically indefensible

This post is a response to a post by Daniel Lakens, “One-sided tests: Efficient and Underused”, whom I greatly respect and, apparently up until now, always vehemently agreed with. So this post is partly an opportunity for him and others to explain where I’m wrong, so dear reader, if you would take this time to point that out, I would be most grateful. Alternatively, telling me I’m right is also very much appreciated of course :-) In any case, if you haven’t done so yet, please read Daniel’s post first (also, see below this post for an update with more links and the origin of this discussion).