What does a meta-analysis do?

A meta-analysis is a statistical technique that combines the results of multiple studies to arrive at a comprehensive conclusion on a particular research question. By pooling data from various studies, a meta-analysis can provide a more precise estimate of the effect size or outcome of interest, increasing statistical power and addressing variability among individual studies. This process helps to quantify the evidence on a particular topic, allowing researchers to identify trends, consensus, or discrepancies within the existing literature.

The power of a meta-analysis lies in its ability to synthesize findings from disparate studies, which may have varying sample sizes, methodologies, and populations, thereby offering a more robust conclusion than what any single study could provide on its own. This is particularly valuable in fields like medicine and psychology, where multiple clinical trials may be conducted that address the same question. By analyzing this collective body of evidence, researchers can better understand the overall efficacy or safety of an intervention, treatment, or phenomenon of interest.

In contrast, critiques of methodology, summarizing expert opinions, or collecting anecdotal evidence represent different approaches that do not statistically synthesize data and thus do not fulfill the role of a meta-analysis. These approaches are valuable in their own right, but they do not provide the same level of rigorous statistical aggregation that character