Module 8: Multilevel modelling in practice: Research questions, data preparation and analysis

In this module we consider the whole process of conducting a research project using multilevel modelling, taking as an example a study of ethnic differences in educational achievement and progress. The research process starts with the formulation of research questions as hypotheses that can be tested using multilevel models. The next step is to prepare the dataset for analysis, which includes decisions about issues such as coding variables, deriving new variables and handling missing data. The analysis then begins with a detailed exploration of the data before fitting multilevel models, building model complexity gradually. We show how the research process is iterative with the results from initial analyses leading to refinements in the original research questions.