Yes, some of Greg’s examples point to the variance being underestimated, but the problem does not inherently come from the idea of using the distribution of effects as the prior, since that should include both the sampling uncertainty and true heterogeneity. That would be the appropriate approach even under a random effects model (I think; I’m more used to thinking in terms of Bayesian hierarchical models and the equivalence might not hold)
Yes, some of Greg’s examples point to the variance being underestimated, but the problem does not inherently come from the idea of using the distribution of effects as the prior, since that should include both the sampling uncertainty and true heterogeneity. That would be the appropriate approach even under a random effects model (I think; I’m more used to thinking in terms of Bayesian hierarchical models and the equivalence might not hold)