
Multilevel Modeling Methods with Introductory and Advanced Applications
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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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Content
- Cover
- Series page
- Multilevel Modeling Methods With Introductory and Advanced Applications
- Library of Congress Cataloging-in-Publication Data
- Dedication
- Contents
- ACKNOWLEDGMENTS
- CHAPTER 1: Introduction to Multilevel Modeling Methods
- SECTION I: ORGANIZATIONAL DATA
- CHAPTER 2: Introduction to Multilevel Models for Organizational Data
- CHAPTER 3: Evaluation of Model Fit and Adequacy
- CHAPTER 4: Causal Inference in Multilevel Settings
- CHAPTER 5: Statistical Power for Linear Multilevel Models
- CHAPTER 6: Cross-Classified Random-Effects Models
- CHAPTER 7: Multilevel Logistic and Ordinal Models
- CHAPTER 8: Single and Multilevel Models for Counts
- SECTION II: LONGITUDINAL DATA
- CHAPTER 9: Individual Growth Curve Models for Longitudinal Data
- CHAPTER 10: Modeling Nonlinear Longitudinal Change With Mixed Effects Models
- CHAPTER 11: Within-Subject Residual Variance-Covariance Structures
- CHAPTER 12: Modeling Variation in Intensive Longitudinal Data
- SECTION III: DESIGN AND SPECIAL ISSUES
- CHAPTER 13: Using Large-Scale Complex Sample Datasets in Multilevel Modeling
- CHAPTER 14: Common Measurement Issues in a Multilevel Framework
- CHAPTER 15: Missing Data Handling for Multilevel Data
- CHAPTER 16: Multilevel Mediation Analysis
- CHAPTER 17: Reporting Results of Multilevel Designs
- ABOUT THE CONTRIBUTORS
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