The SAGE Handbook of Multilevel Modeling

ISBN 13: 9780857025647

The SAGE Handbook of Multilevel Modeling

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9780857025647: The SAGE Handbook of Multilevel Modeling
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...This handbook attempts to cover an intricate and multifaceted topic and delivers what is expected of it very successfully and at good cost considering its all-purpose usefulness. This handbook is a must-have consultation book for researchers interested in multilevel modelling from a wide variety of disciplines, if not all. (Patricio Troncosco, Cathie Marsh Institute for Social Research, The University of Manchester)

Reseña del editor:

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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Publicado por Sage Publications Ltd, United Kingdom (2013)
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Descripción Sage Publications Ltd, United Kingdom, 2013. Hardback. Condición: New. Language: English . Brand New Book. 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. Nº de ref. del artículo: AAX9780857025647

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Marc A. Scott (editor), Jeffrey S. Simonoff (editor), Brian D. Marx (editor)
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Publicado por Sage Publications Ltd, United Kingdom (2013)
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Descripción Sage Publications Ltd, United Kingdom, 2013. Hardback. Condición: New. Language: English . Brand New Book. 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. Nº de ref. del artículo: AAX9780857025647

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Marc A. Scott
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