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Todd D. Little, Kai U. Schnabel, Jrgen Baumert - Modeling Longitudinal and Multilevel Data, Häftad

Häftad, Engelska, 2014

Modeling Longitudinal and Multilevel Data

Practical Issues, Applied Approaches, and Specific Examples

Av Todd D. Little, Kai U. Schnabel, Jrgen Baumert

910 kr

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Beskrivning
This book focuses on the practical issues and approaches to handling longitudinal and multilevel data. All data sets and the corresponding command files are available via the Web. The working examples are available in the four major SEM packages--LISREL, EQS, MX, and AMOS--and two Multi-level packages--HLM and MLn. All equations and figural conventions are standardized across each contribution. The material is accessible to practicing researchers and students. Users can compare and contrast various analytic approaches to longitudinal and multiple-group data including SEM, Multi-level, LTA, and standard GLM techniques. Ideal for graduate students and practicing researchers in social and behavioral sciences.
Produktinformation
  • Utgivningsdatum: 2014-12-22
  • Mått: 152 x 229 x 16 mm
  • Vikt: 408 g
  • Format: Häftad
  • Språk: Engelska
  • Antal sidor: 304
  • Förlag: Taylor & Francis Ltd
  • ISBN: 9781138012530
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Todd D. Little (Edited by) ,  Kai U. Schnabel (Edited by) ,  Jurgen Baumert (Edited by)

Recensioner i media

"This book is well written in an accessible style, and it will clearly appeal to researchers with a social and psychological interest."—The Statistician"Investigators conducting longitudinal research should find this book useful."—Journal of Mathematical Psychology"...I consider this book to be an extremely useful resource providing a great deal of depth in the topics of multilevel and longitudinal modeling. Because many of the topics included in this book are cutting-edge methodological advances, the book will be most appreciated by researchers who already have a good grasp of multilevel and longitudinal approaches. For this group of individuals, the book will be a very valuable resource.—Organizational Research Methods

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