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Furthermore, Bayesian approaches facilitate sensitivity analyses through adjusting prior specification, and permit the the robustness of fitted models to be evaluated. This is particularly useful when few studies are available and estimated parameters of one- and two-stage models may be severely biased due to estimation difficulties.

Future research is needed to evaluate the performance of the described methods, and to compare their accuracy and coverage with Bayesian alternatives. However, we generally recommend that a one-stage IPD-MA method is used as this models the exact binomial distribution, accounts for within-study parameter correlation, offers more flexibility in the model specification and avoids continuity corrections.

It is therefore particularly preferable when few studies or few events in some studies are available.