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. ​

Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.

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.

This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

This book provides a uniquely accessible introduction to multilevel modeling, a powerful tool for analyzing relationships between an individual-level dependent variable, such as student reading achievement, and individual-level and contextual explanatory factors, such as gender and neighborhood quality. Helping readers build on the statistical techniques they already know, Robert Bickel emphasizes the parallels with more familiar regression models, shows how to do multilevel modeling using SPSS, and demonstrates how to interpret the results. He discusses the strengths and limitations of multilevel analysis and explains specific circumstances in which it offers (or does not offer) methodological advantages over more traditional techniques. Over 300 dataset examples from research on educational achievement, income attainment, voting behavior, and other timely issues are presented in numbered procedural steps.

The goal of this book is multidimensional: a) to help reviving Statistics education in many parts in the world where it is in crisis. For the first time authors from many developing countries have an opportunity to write together with the most prominent world authorities. The editor has spent several years searching for the most reputable statisticians all over the world. International contributors are either presidents of the local statistical societies, or head of the Statistics department at the main university, or the most distinguished statisticians in their countries. b) to enable any non-statistician to obtain quick and yet comprehensive and highly understandable view on certain statistical term, method or application c) to enable all the researchers, managers and practicioners to refresh their knowledge in Statistics, especially in certain controversial fields. d) to revive interest in statistics among students, since they will see its usefulness and relevance in almost all branches of Science.

This book provides an original framework to assess public investment policies co-financed by Union (Federal) governments. This framework is applied to two important case studies: the EU Cohesion Policy and the US Federal Investment Policies. Cost-Benefit Analysis of Multi-Level Government sheds light on a number of outstanding issues of economic theory by extending the theory of shadow prices, and provides guidance to real-world decision makers. In particular, the following questions are addressed: Under which theoretical circumstances, higher level government intervention in Member States through investment policies is justified? Is there any new welfare economics rationale underpinning interregional equity? What is the relationship between interregional and interpersonal income distribution? How can social exclusion be included in cost-benefit tests? How can higher level government budget funds to investment policies before it bargains programming documents with lower tiers of government by considering also their response function? In these circumstances, how can optimal matching rates be derived assuming binding and non binding budgetary constraints? Can such a theoretical framework be applied for guidance to real-world decision makers? The book will be of interest to policy makers, postgraduate students and researchers in cost-benefit analysis, welfare economics, public choice, public finance, multi-level government economics, and income distribution issues.

This book provides a broad overview of basic multilevel modeling issues and illustrates techniques building analyses around several organizational data sets. Although the focus is primarily on educational and organizational settings, the examples will help the reader discover other applications for these techniques. Two basic classes of multilevel models are developed: multilevel regression models and multilevel models for covariance structures--are used to develop the rationale behind these models and provide an introduction to the design and analysis of research studies using two multilevel analytic techniques--hierarchical linear modeling and structural equation modeling.

This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the biomedical sciences. The chapter authors are all leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is essential for empirical researchers in these fields.

This volume is designed as a basic text for upper level and graduate courses in contemporary sociological theory. Most sociology programs require their majors to take at least one course in sociological theory, sometimes two. A typical breakdown is between classical and contemporary theory. Theory is perhaps one of the bro- est areas of sociological inquiry and serves as a foundation or framework for more specialized study in specific substantive areas of the field. In addition, the study of sociological theory can readily be related to various aspects of other social science disciplines as well. From the very beginning sociology has been characterized by alternative theoretical perspectives. Classical theory includes the European founding figures of the dis- pline whose works were produced during the later half of the nineteenth century and the first couple of decades of the twentieth century plus early American th- rists. For most of the second half of the twentieth century, a fairly high consensus has developed among American sociologists regarding these major founders, p- ticularly with regard to the works of Durkheim and Weber in analyzing the overall society and of Simmel in analyzing social interaction processes. Since the late 1960s and early 1970s the influence of Marx has also been recognized. Recent decades have also witnessed an increased emphasis on the important contributions of several pioneering feminist perspectives in the early years of sociology.