Estimating association between Facebook adoption and well-being in 72 countries

It's like estimating the health effects of automobile pollution by comparing the health of people with driver licenses against people who don't have driver licenses. Since automobile pollution harms both groups, you might not see large differences between the groups, even though pollution is very harmful to everyone's health.

- a bayesian mixed model is just what I would have used here, great choice and a good sign for power

- the effect sizes are definitely very small. I would not overstate the story here.

That said, I also don't believe that facebook is the primary story here, because other findings all suggest tiny effect sizes (see the famous emotional contagion experiment) and because we don't have a clear, convincing theoretical model IMO. There are just so many intra-individual confounders that would need to be included, including some that have dynamic, self-reinforcing effects.

Still, great to have more robust work here.

[edit] PS: just to throw a methodological nitpick out: Some bayesians are going to have a heart attack while reading "the uncertainty cutoff of 97.5% for posterior probabilities".