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The primary aim of a meta-analysis is to statistically combine data from multiple trials that address the same research question. This technique allows researchers to increase the overall power and reliability of the findings by aggregating data from various studies, which may have smaller sample sizes individually. By synthesizing results, meta-analysis provides a more comprehensive understanding of the effects or outcomes related to a specific intervention or treatment, offering insights that might not be apparent from individual studies alone. It helps identify trends, assess consistency among trial results, and establish more robust conclusions regarding efficacy and safety.

In contrast, other options are focused on specific aspects of research that do not capture the comprehensive nature of a meta-analysis. Approving new medications for market is the role of regulatory agencies and is not the aim of meta-analysis. Evaluating qualitative data typically involves a different methodological approach rather than the statistical aggregation that characterizes meta-analysis. Analyzing clinical outcomes over time may involve longitudinal studies but is not specifically tied to the process of combining results from multiple trials as done in meta-analysis.