In this video, the impact of non-independent evidence of observations on regression analysis and what kind of problems it might cause for empirical analysis are discussed with the help of several examples. Non-independent observations violate the assumption of independence of observations in regression analysis. This can occur when observations are clustered or dependent, resulting in interclass correlation. As interclass correlation increases, estimates become less precise, although they remain unbiased and consistent.
Slides: osf.io/ex2g8