9781841697222-1841697222-Handbook of Advanced Multilevel Analysis (European Association of Methodology Series)

Handbook of Advanced Multilevel Analysis (European Association of Methodology Series)

ISBN-13: 9781841697222
ISBN-10: 1841697222
Edition: 1
Author: Joop Hox, J. Kyle Roberts
Publication date: 2010
Publisher: Routledge
Format: Hardcover 408 pages
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Book details

ISBN-13: 9781841697222
ISBN-10: 1841697222
Edition: 1
Author: Joop Hox, J. Kyle Roberts
Publication date: 2010
Publisher: Routledge
Format: Hardcover 408 pages

Summary

Handbook of Advanced Multilevel Analysis (European Association of Methodology Series) (ISBN-13: 9781841697222 and ISBN-10: 1841697222), written by authors Joop Hox, J. Kyle Roberts, was published by Routledge in 2010. With an overall rating of 4.0 stars, it's a notable title among other Research (Psychology & Counseling) books. You can easily purchase or rent Handbook of Advanced Multilevel Analysis (European Association of Methodology Series) (Hardcover, Used) from BooksRun, along with many other new and used Research books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This new handbook is the definitive resource on advanced topics related to multilevel analysis. The editors assembled the top minds in the field to address the latest applications of multilevel modeling as well as the specific difficulties and methodological problems that are becoming more common as more complicated models are developed. Each chapter features examples that use actual datasets. These datasets, as well as the code to run the models, are available on the book’s website http://www.hlm-online.com . Each chapter includes an introduction that sets the stage for the material to come and a conclusion.

Divided into five sections, the first provides a broad introduction to the field that serves as a framework for understanding the latter chapters. Part 2 focuses on multilevel latent variable modeling including item response theory and mixture modeling. Section 3 addresses models used for longitudinal data including growth curve and structural equation modeling. Special estimation problems are examined in section 4 including the difficulties involved in estimating survival analysis, Bayesian estimation, bootstrapping, multiple imputation, and complicated models, including generalized linear models, optimal design in multilevel models, and more. The book’s concluding section focuses on statistical design issues encountered when doing multilevel modeling including nested designs, analyzing cross-classified models, and dyadic data analysis.

Intended for methodologists, statisticians, and researchers in a variety of fields including psychology, education, and the social and health sciences, this handbook also serves as an excellent text for graduate and PhD level courses in multilevel modeling. A basic knowledge of multilevel modeling is assumed.

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