Multilevel Models Explained
Multilevel models address the common assumption that observations are independent, which often isn't true in real-world scenarios. When individuals share environments—like siblings, classmates, or patients—their similarities can lead to correlated data that standard methods overlook. This oversight can result in overconfidence in statistical estimates, highlighting the importance of considering these relationships in model design.In this clip
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