COLLEGE PARK, MD (January, 2016) In December, Information Age published Advances in Multilevel Modeling for Educational Research: Addressing Practical Issues Found in Real-World Applications, the latest volume in the CILVR Series on Latent Variable Methodology. The book was edited by Drs. Jeffrey Harring and Laura Stapleton of the Measurement, Statistics, and Evaluation (EDMS) program in collaboration with Dr. Natasha Beretvas of the University of Texas at Austin.
Multilevel modeling has become increasingly popular among educational practitioners and researchers as a way to account for nested sampling designs that often accompany data collection in classrooms, schools, and districts. A number of education research articles adopt multilevel models as their primary modeling framework, and governmental funding agencies advocate the use of multilevel models as part of a comprehensive analytic strategy for conducting rigorous and relevant research to improve the nation’s education system.
Intended for advanced graduate students, faculty, and researchers interested in multilevel data analysis, Advances in Multilevel Modeling is a valuable resource for any research area that uses hierarchically nested data, including education policy and administration, educational psychology (including school psychology and special education), and clinical psychology. 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.
Advances in Multilevel Modeling is comprised of contributions from attendees of the Center for Integrated Latent Variable Research’s (CILVR) November 2014 conference, described in the fall 2015 issue of Endeavors. The conference’s keynote speaker, Dr. Sophia Rabe-Hesketh of the University of California, Berkeley, penned the book’s foreword. In addition to Drs. Harring and Stapleton, contributors from the University of Maryland include Drs. Ji Seung Yang, Hong Jiao, and Tracy Sweet, as well as EDMS doctoral students Qiwen Zheng and Daniel Lee.
The CILVR Series on Latent Variable Methodology is edited by Dr. Gregory Hancock.
Click here to learn more about Advances in Multilevel Modeling for Education Research on the publisher’s website. The book is also available at Amazon.com.
Dr. Jeffrey Harring is an associate professor in the Measurement, Statistics, and Evaluation program in the Department of Human Development and Quantitative Methodology. His research focuses on applications of statistical models for repeated measures data, nonlinear structural equation models, and statistical computing.
Dr. Laura Stapleton is an associate professor in the Measurement, Statistics, and Evaluation program in the Department of Human Development and Quantitative Methodology. Her work looks at analysis of administrative and survey data obtained under complex sampling designs and multilevel latent variable models, including tests of mediation within a multilevel framework. She is the associate director of research for the Maryland State Longitudinal Data System Center.
Dr. Gregory Hancock is a professor in the Department of Human Development and Quantitative Methodology, where he directs the Measurement, Statistics, and Evaluation program (EDMS) and the Center for Integrated Latent Variable Research (CILVR).
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