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Pooled analyses involve collecting and combining individual data from multiple studies into one comprehensive dataset. This approach allows researchers to integrate findings from different studies, thereby increasing the sample size and enhancing the statistical power of the analysis. By pooling data, it becomes possible to explore more nuanced relationships, assess variability, and improve the overall validity of the results.

In this context, researchers can analyze the combined dataset to draw more robust conclusions that may not be evident from smaller, individual studies alone. This technique is particularly useful in fields such as health education and epidemiology, where diverse studies may focus on similar outcomes or populations, enabling a more complete understanding of a research question.

The other choices do not accurately reflect the process of pooled analyses. Aggregating qualitative data pertains to synthesizing non-numeric data, while analyzing data from a single comprehensive study refers to a different research approach. Conducting a systematic literature review involves summarizing existing research rather than combining datasets from multiple studies.