Multilevel analysis, also known as hierarchical linear modeling, is a statistical technique used to analyze data that are nested or have a hierarchical structure. This method allows researchers to examine relationships at multiple levels of analysis simultaneously, such as within individuals, within groups, and between groups. It is commonly used in social sciences, education, and health research to account for the complexities of nested data and to estimate the effects of different levels of variables on outcomes. Multilevel analysis is particularly useful for studying how factors at different levels of analysis interact and influence each other.