The topic of this book is multilevel analysis but, although this is a mathematical topic, it has been written by an epidemiologist. This could, perhaps, be a disadvantage, because the mathematical background of multilevel analysis will not be discussed in detail. However, it can also be seen as an advantage, because it implies that the emphasis of this book lies more on the application of multilevel analysis. Many books have been written on multilevel analysis, but most (all) of them have been written by statisticians, and therefore they mainly focus on the mathematical background of multilevel analysis. The problem with that approach is that such books are very difficult for nonmathematical researchers to understand. And yet, these non-mathematical researchers are expected to use multilevel analysis to analyse their data. In fact, a researcher is not primarily interested in the basic (difficult) mathematical background of the statistical methods, but in finding correct answers to research questions. Furthermore, researchers want to know how to apply a statistical technique and how to interpret the results. Due to their different basic interests and different levels of thinking, communication problems between statisticians and epidemiologists are quite common, and they often communicate on different levels. This, in addition to the growing interest in multilevel analysis, initiated the writing of this book. This book is written for ‘non-statistical’ researchers, and it aims to provide a practical guide as to when and how to use multilevel analysis. The purpose of this book is to build a bridge between the different communication levels that exist between statisticians and researchers when addressing the topic of multilevel analysis.