Generalized linear mixed models (GLMMs) extend generalized linear models by incorporating both fixed and random effects, allowing for the analysis of correlated and non-normally distributed data. They are particularly useful in handling hierarchical or grouped data structures, making them a powerful tool for complex data analysis in various fields such as ecology, medicine, and social sciences.