Advances in multilevel modeling for educational research : addressing practical issues found in real-world applications / edited by Jeffrey R. Harring, Laura M. Stapleton, S. Natasha Beretvas.

Includes bibliographical references.

The Discrepancy between Measurement and Modeling in Longitudinal Data Analysis / Daniel J. Bauer and Patrick J. Curran -- Incomplete Multilevel Data : Problems and Solutions / Joop Hox, Stef van Buuren, and Shahab Jolani -- Sampling Weight Considerations for Multilevel Modeling of Panel Data / Laura M. Stapleton, Jeffrey R. Harring, and Daniel Y. Lee -- Residual Diagnostics and Model Assessment in a Multilevel Framework : Recommendations toward Best Practice / Ann A. O'Connell, Gloria Yeomans-Maldonado, and D. Betsy McCoach -- Multilevel Cross-Classified Testlet Model for Complex Item and Person Clustering in Item Response Data Analysis / Hong Jiao, Akihito Kamata, and Chao Xie -- General Random Effect Latent Variable Modeling : Random Subjects, Items, Contexts, and Parameters / Tihomir Asparouhov and Bengt Muth�en -- N-Level Structural Equation Model of Student Achievement Data Nested with Repeated Teachers, Schools, and Districts / Paras D. Mehta and Yaacov Petscher -- A Model for Cross-Classified Nested Repeated Measures Data / Jeffrey R. Harring, S. Natasha Beretvas, and Anita Israni -- Cross-classified Random Effects Models for Assessing Rater Severity and Differential Rater Functioning / S. Natasha Beretvas, Daniel L. Murphy, and Matthew N. Gaertner -- Handling Measurement Error in Predictors with a Multilevel Latent Variable : Plausible Values Approach / Ji Seung Yang and Michael Seltzer -- Mixture Modeling Methods for Causal Inference with Multilevel Data / Jee-Seon Kim, Peter M. Steiner, and Wen-Chiang Lim -- Multilevel Social Network Models : Incorporating Network-Level Covariates into Hierarchical Latent Space Models / Tracy Sweet and Qiwen Zheng.

Advances in Multilevel Modeling for Educational Research: Addressing Practical Issues Found in Real-World Applications is a resource intended for advanced graduate students, faculty and/or researchers interested in multilevel data analysis, especially in education, social and behavioral sciences. The chapters are written by prominent methodological researchers across diverse research domains such as educational statistics, quantitative psychology, and psychometrics. Each chapter exposes the reader to some of the latest methodological innovations, refinements and state-of-the-art developments and perspectives in the analysis of multilevel data including current best practices of standard techniques. We believe this volume will be particularly appealing to researchers in domains including but not limited to: educational policy and administration, educational psychology including school psychology and special education, and clinical psychology. In fact, we believe this volume will be a desirable resource for any research area that uses hierarchically-nested data. The book will likely be attractive to applied and methodological researchers in several professional organizations such as the American Educational Research Association (AERA), the American Psychological Association (APA), the American Psychological Society (APS), the Society for Research on Educational Effectiveness (SREE), and other related organizations.