• Summary
  • Contents
  • Subject index

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 ...

Multilevel Models in the Social and Behavioral Sciences
Multilevel models in the social and behavioral sciences
DavidRindskopfCUNY Graduate Center, USA
29.1 Overview

Multilevel models were developed and adopted very quickly in the social sciences during the 1980s and 1990s. Two factors seem to have caused this rapid change. First, social scientists generally knew that nested data should not be treated as if the observations were independent, but had been stymied by the lack of algorithms or software to treat the data correctly. Secondly, new ways of thinking about these models contributed to their quick adoption: rather than being just statistical necessities, the models could be expressed in ways that gave the parameters interesting and useful subject-matter interpretations. This interpretation arose in sociology through the work of William Mason ...

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