I am tired of reading and reviewing academic studies using mediation analysis, especially when researchers are relying on cross-sectional, observational data. None mentioned, none forgotten. In the best possible world, people would read more Pearl and understand the challenges of demonstrating empirical evidence in line with causal pathways (and maybe reconsider whether they want to do a mediation analysis at all).
However, I am very much aware that researchers will need to do mediation analyses. You gotta do what you gotta do to satisfy Reviewer 2. In this post, I recommend a few studies that I hope people will read before they conduct a mediation analysis. Without further ado, here are my recommendations:
– Explaining Causal Findings Without Bias: Detecting and Assessing Direct Effects (Acharya et al. 2016)
– Yes, but what’s the mechanism? (don’t expect an easy answer) (Bullock et al. 2010)
– Enough Already about “Black Box” Experiments: Studying Mediation Is More Difficult than Most Scholars Suppose (Green et al. 2010)
– The Mediation Myth (Kline 2015)
– Unwarranted inferences from statistical mediation tests – An analysis of articles published in 2015 (Fiedler et al. 2018)
– Causal Mediation Analysis: Warning! Assumptions Ahead (Keele 2015)
– Power Anomalies in Testing Mediation (Kenny and Judd 2014)
– The “Goldilocks Zone”: (Too) many confidence intervals in tests of mediation just exclude zero (Götz et al. 2021)