Robust variance estimation (RVE; Hedges, Tipton, & Johnson, 2010) produces asymptotically valid standard errors and hypothesis tests, **even if the error structure is mis-specified**.

- Accurate estimates of correlations between effect sizes are not needed.
- Meta-regressions estimated by weighted least squares (just like model-based multivariate meta-regression).
- Weights can be based on effect size variances and rough imputations of correlations.
- But exact inverse-variance weights are not needed.

- Variances of meta-regression coefficients estimated using a "sandwich" formula (Liang & Zeger, 1986).