The SAGE Handbook of Multilevel Modeling - Softcover

 
9780857025647: The SAGE Handbook of Multilevel Modeling

Inhaltsangabe

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.

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Über die Autorin bzw. den Autor

Marc A. Scott is an Associate Professor of Applied Statistics at New York University′s Steinhardt School of Culture, Education, and Human Development and co-directs the Center for the Promotion of Research Involving Innovative Statistical Methodology (PRIISM).

Jeffrey S. Simonoff is Professor of Statistics in the Department of Information, Operations and Management Sciences of the Leonard N. Stern School of Business at New York University.

Brian D. Marx is Professor of Statistics in the Department of Experimental Statistics at Louisiana State University.

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Leading contributors combine practical pieces with overviews of the state of the art in the field, making this handbook essential reading for any student or researcher looking to apply multilevel techniques in their own research

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