Multilevel modeling is a statistical technique used to analyze data that is organized at more than one level, such as individuals nested within groups. This approach allows researchers to account for the variability at different levels, making it particularly useful for understanding complex data structures, like those often found in longitudinal surveys where measurements are taken over time.
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