In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling. The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field. Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference. Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models. Part III includes discussion of missing data and robust methods, assessment of fit and software. Part IV consists of exemplary modeling and data analyses written by methodologists working in specific disciplines. Combining practical pieces with overviews of the field, this Handbook is essential reading for any student or researcher looking to apply multilevel techniques in their own research.

In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling. The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field. Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference. Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models. Part III includes discussion of missing data and robust methods, assessment of fit and software. Part IV consists of exemplary modeling and data analyses written by methodologists working in specific disciplines. Combining practical pieces with overviews of the field, this Handbook is essential reading for any student or researcher looking to apply multilevel techniques in their own research.

This handbook focuses on core micro organizational behaviour issues, providing students and scholars with an insightful and wide-reaching survey of the state of the field.

This handbook is organised into four sections on theory and methods, aging and the social structure, social factors and social institutions and aging and social intervention.

The Encyclopedia of Statistics in Behavioral Science encompasses the refined statistical concepts and techniques that are essential to the advancement in psychology and its ever-widening fields of application. Providing comprehensive accounts drawn from the huge expansion of statistical methodologies in the behavioral sciences, highlighting new techniques and developments from the past decade. Up-to-date coverage of developing fields including neuroscience, behavioral genetics, decision learning and cognitive science. Containing over 600 articles and over 400 contributions from eminent psychologists and statisticians world-wide. Emphasis on practical, non-technical methods with wide ranging application. Extensively cross-referenced to ensure fast and accurate access to available information Representing an invaluable addition to both the psychological and statistical literature, the Encyclopedia of Statistics in Behavioral Science forms an essential reference work for researchers, educators and students in the fields of applied psychology, sociology, market research, consumer behavior, management science, decision making and human resource management. For further details please visit: www.wiley.com/go/eosbs