The purpose of the multilevel approach is to understand individual behaviors taking into account the social context in which they occur. This book deals with concepts and methods underlying this approach. This book is of interest to a broad audience of social scientists, statisticians and philosophers concerned with new issues raised by the multilevel approach, and more generally with explanation in the social sciences.

The purpose of the multilevel approach is to understand individual behaviors taking into account the social context in which they occur. This book deals with concepts and methods underlying this approach. This book is of interest to a broad audience of social scientists, statisticians and philosophers concerned with new issues raised by the multilevel approach, and more generally with explanation in the social sciences.

This volume provides new insights into the functioning of organizational, managerial and market societies. Multilevel analysis and social network analysis are described and the authors show how they can be combined in developing the theory, methods and empirical applications of the social sciences. This book maps out the development of multilevel reasoning and shows how it can explain behavior, through two different ways of contextualizing it. First, by identifying levels of influence on behavior and different aggregations of actors and behavior, and complex interactions between context and behavior. Second, by identifying different levels as truly different systems of agency: such levels of agency can be examined separately and jointly since the link between them is affiliation of members of one level to collective actors at the superior level. It is by combining these approaches that this work offers new insights. New case studies and datasets that explore new avenues of theorizing and new applications of methodology are presented. This book will be useful as a reference work for all social scientists, economists and historians who use network analyses and multilevel statistical analyses. Philosophers interested in the philosophy of science or epistemology will also find this book valuable. ​

This book presents a historical panorama of the evolution of demographic thought from its eighteenth-century origins up to the present day. The book uses this to demonstrate how the multilevel approach can resolve some of the contradictions that have become apparent and achieve a synthesis of the different approaches employed. This is both a textbook and an assessment of the multilevel analysis that broadens the scope of demography with its approach.

This leading-edge study focuses on the latest techniques in analysing and representing the complex, multi-layered data now available to geographers studying urban zones and their populations. The volume tracks the successful results of the SPANGEO Project, which was set up in 2005 to standardize, and share, the syncretic, multinational mapping techniques already developed by geographers and computer scientists. SPANGEO sought new and responsive ways of visualising urban geographical and social data that reflected the fine-grained detail of the inputs. It allowed for visual representation of the large and complex networks and flows which are such an integral feature of the dynamism of urban geography. SPANGEO developed through the ‘visual analytics loop’ in which geographers collaborated with computer scientists by feeding data into the design of visualisations that in turn spawned the urge to incorporate more varied data into the visualisation. This volume covers all the relevant aspects, from conceptual principles to the tools of network analysis and the actual results flowing from their deployment. Detailed case studies set out in this volume include spatial multi-level analyses of flows in airports and sea ports, as well as the fascinating scientific networks in European cities. The volume shows how the primary concern of geography—the interaction of society with physical space—has been revivified by the complexities of new cartographical and statistical methodologies, which allow for highly detailed mapping and far more powerful computer analysis of spatial relationships.

Multilevel Modeling Methods with Introductory and Advanced Applications provides a cogent and comprehensive introduction to the area of multilevel modeling for methodological and applied researchers as well as advanced graduate students. The book is designed to be able to serve as a textbook for a one or two semester course in multilevel modeling. The topics of the seventeen chapters range from basic to advanced, yet each chapter is designed to be able to stand alone as an instructional unit on its respective topic, with an emphasis on application and interpretation. In addition to covering foundational topics on the use of multilevel models for organizational and longitudinal research, the book includes chapters on more advanced extensions and applications, such as cross-classified random effects models, non-linear growth models, mixed effects location scale models, logistic, ordinal, and Poisson models, and multilevel mediation. In addition, the volume includes chapters addressing some of the most important design and analytic issues including missing data, power analyses, causal inference, model fit, and measurement issues. Finally, the volume includes chapters addressing special topics such as using large-scale complex sample datasets, and reporting the results of multilevel designs. Each chapter contains a section called Try This!, which poses a structured data problem for the reader. We have linked our book to a website (http://modeling.uconn.edu) containing data for the Try This! section, creating an opportunity for readers to learn by doing. The inclusion of the Try This! problems, data, and sample code eases the burden for instructors, who must continually search for class examples and homework problems. In addition, each chapter provides recommendations for additional methodological and applied readings.

Applauded for its clarity, this accessible introduction helps readers apply multilevel techniques to their research. The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software.