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Meta‐analysis allows for the aggregation of results from multiple studies to improve statistical inference for the parameter of interest. In recent years, random‐effect meta‐analysis has been employed to synthesize estimates of incidence rates of adverse events across heterogeneous clinical trials to evaluate treatment safety. However, the validity of existing approaches relies on asymptotic approximation...
We describe an exact, unconditional, non‐randomized procedure for producing confidence intervals for the grand mean in a normal‐normal random effects meta‐analysis. The procedure targets meta‐analyses based on too few primary studies, , say, to allow for the conventional asymptotic estimators, e.g., DerSimonian and Laird (1986), or non‐parametric resampling‐based procedures, e.g., Liu et al. (2017)...
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