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Handbook of Multilevel Analysis [Hardcover]

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  • Category: Books (Mathematics)
  • ISBN-10:  0387731830
  • ISBN-10:  0387731830
  • ISBN-13:  9780387731834
  • ISBN-13:  9780387731834
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  494
  • Pages:  494
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Mar-2007
  • Pub Date:  01-Mar-2007
  • SKU:  0387731830-11-SPRI
  • SKU:  0387731830-11-SPRI
  • Item ID: 100793270
  • List Price: $169.99
  • Seller: ShopSpell
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  • Delivery by: Jan 20 to Jan 22
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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 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 bio-medical sciences. The models used for this type of data are linear and nonlinear regression models that account for observed and unobserved heterogeneity at the various levels in the data.

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. The authors of the chapters are the leading experts in the field.

Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is useful for empirical researchers in these fields. Prior knowledge of multilevel analysis is not required, lS$

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