rchical-bayesian-random-effects-meta-analysis"></a>
</h4>
<p>Second, we account for the clustered effect size estimates within
districts by extending the previous function call with the
<code>study_ids = dat$district</code> argument. This allows us to
estimate the hierarchical Bayesian random effects meta-analysis
(corresponding to <code>fit_metafor</code>). We use the default prior
distribution for the correlation parameter
<code>\rho \sim \text{Beta}(1, 1)</code>, set via the
<code>priors_hierarchical</co