Mixed models are statistical models that incorporate both fixed effects, which are consistent and predictable, and random effects, which are subject to variability and randomness across different levels of data hierarchy. They are particularly useful for analyzing data with complex structures, such as longitudinal data or data with nested or grouped observations, allowing for more accurate and generalizable inferences.