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Multilevel Modeling Methods with Introductory and Advanced Applications (Quantitative Methods in Education and the Behavioral Sciences: Issues, Research, and Teaching)

By: Ann A. O'Connell (Edited by) , Bethany A. Bell (Edited by) , D. Betsy McCoach (Edited by)

Extended Catalogue

Ksh 22,800.00

Format: Hardback or Cased Book

ISBN-10: 1648028721

ISBN-13: 9781648028724

Collection / Series: Quantitative Methods in Education and the Behavioral Sciences: Issues, Research, and Teaching

Collection Type: Publisher collection

Publisher: Emerald Publishing Inc

Imprint: Information Age Publishing

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Mar 17th, 2022

Publication Status: Active

Product extent: 644 Pages

Weight: 1073.00 grams

Dimensions (height x width x thickness): 23.40 x 15.60 x 3.50 cms

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"Multilevel Modeling Methods" introduces multilevel modeling for researchers and advanced students. It serves as a textbook for courses, covering topics from basic to advanced, including organizational and longitudinal research, advanced applications, design issues, and special topics like large-scale datasets and reporting results.

Multilevel Modeling Methods with Introductory and Advanced Applications provides a cogent and comprehensive introduction to the area of multilevel modeling for methodological and applied researchers as well as advanced graduate students. The book is designed to be able to serve as a textbook for a one or two semester course in multilevel modeling. The topics of the seventeen chapters range from basic to advanced, yet each chapter is designed to be able to stand alone as an instructional unit on its respective topic, with an emphasis on application and interpretation.

In addition to covering foundational topics on the use of multilevel models for organizational and longitudinal research, the book includes chapters on more advanced extensions and applications, such as cross-classified random effects models, non-linear growth models, mixed effects location scale models, logistic, ordinal, and Poisson models, and multilevel mediation. In addition, the volume includes chapters addressing some of the most important design and analytic issues including missing data, power analyses, causal inference, model fit, and measurement issues. Finally, the volume includes chapters addressing special topics such as using large-scale complex sample datasets, and reporting the results of multilevel designs.

Each chapter contains a section called Try This!, which poses a structured data problem for the reader. We have linked our book to a website (http://modeling.uconn.edu) containing data for the Try This! section, creating an opportunity for readers to learn by doing. The inclusion of the Try This! problems, data, and sample code eases the burden for instructors, who must continually search for class examples and homework problems. In addition, each chapter provides recommendations for additional methodological and applied readings.


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