Multilevel Analysis

Demographers describe and analyse individual events at multiple levels of observation that range from the individuals themselves to the overall population of interest. In quantitative population studies, one way to streamline investigation is to perform a multilevel statistical analysis using a single model, which improves the accuracy of the estimates and therefore of the results.
To that end, this book guides the reader through the first stages of multilevel analysis, from design to implementation, with step-by-step explanations on how to navigate the three most common statistical software environments (Stata®, SAS®, and R). Concrete examples based on census data are provided using an analysis of school enrolment in rural Kenya.
Intended for all statistical database users seeking to develop or expand their knowledge of multilevel analysis, this manual details and illustrates the procedures for creating multilevel models and discusses their prerequisites, advantages, and limitations. Suggestions for further reading are also provided.

Arnaud Bringé heads the Statistical Methods Department at the French Institute for Demographic Studies (INED), where he and his team lend support in establishing consistent statistical databases while training researchers in statistical methodologies and tools. He contributes to developing solutions for survey data analysis and to monitoring research projects.

Valérie Golaz is an INED researcher and currently a visiting scholar at the Population–Environment–Development Laboratory (LPED) (Aix-Marseille Université/IRD) who specializes in methods for collecting and analysing qualitative and quantitative demographic data. Her work focuses on social transformation and environmental change in contexts of high population growth in the Global South.

Paul Reeves tranlator

This book is an English translation of Manuel pratique d’analyse multiniveau (Paris, INED, 2017)