Random effects are vital in epidemiological studies because they help in managing the heterogeneity inherent in population data. For example, individuals in a study may belong to different geographical locations, healthcare facilities, or socioeconomic strata. Ignoring this variability can lead to misleading conclusions, as it overlooks the influence of these unobserved factors.
