mixed effects models

Mixed effects models are a type of statistical tool used to analyze data that involves multiple sources of variability. They account for both fixed effects (consistent factors of interest, like treatment or age) and random effects (random variations, like differences between individual subjects or groups). This approach helps to understand overall trends while considering individual differences, making it especially useful in fields like medicine or social sciences where data is often collected from diverse groups. By doing so, mixed effects models provide more accurate and flexible analysis compared to simpler models.