Edinburgh Napier University

  Whenever research is concerned with the analysis of relationships between lowerlevel units (e.g., individuals) and the higherlevel unit they belong to (e.g., group), a hierarchical – multilevel or nested – data structure occurs. In such cases, multi‐level modeling (MLM) approaches, also known as hierarchical linear modeling, are suited to empirically assess respective data structures in a methodologically correct way. The article gives an introduction to the background of multilevel modeling, outlines the methodological procedure for the basic case of a two‐level model, and provides an outlook to more advanced applications of MLM.