Researchers have developed a many-to-many-to-many (MMM) mediation analysis framework to study high-dimensional data with multiple exposures, mediators, and outcomes simultaneously. This method enables variable selection for high-dimensional datasets, estimates indirect effect matrices, and enhances prediction accuracy in complex biological pathways, such as genetic influences on brain function and cognitive outcomes. The MMM package offers a robust tool for analyzing intricate multi-layered pathways in scientific research.
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