Why are Multilevel Models Important in Epidemiology?
In epidemiology, data is often collected from multiple sources and levels. For instance, when studying the spread of a disease, data might be collected from individuals, neighborhoods, and cities. Traditional statistical methods may not adequately account for the hierarchical structure of such data, potentially leading to biased estimates and incorrect conclusions. Multilevel models address this issue by allowing for the analysis of data at multiple levels, providing more accurate and reliable results.
