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Multilevel Modeling of Educational Data (Paperback, New)
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Multilevel Modeling of Educational Data (Paperback, New)
Series: Quantitative Methods in Education & the Behavioral Sciences
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A volume in Quantitative Methods in Education and the Behavioral
Sciences: Issues, Research, and Teaching Series Editor Ron Serlin,
University of Wisconsin (sponsored by the Educational
Statisticians, SIG) Multilevel Modeling of Educational Data,
co-edited by Ann A. O'Connell, Ed.D., and D. Betsy McCoach, Ph.D.,
is the next volume in the series: Quantitative Methods in Education
and the Behavioral Sciences: Issues, Research and Teaching
(Information Age Publishing), sponsored by the Educational
Statisticians' Special Interest Group (Ed-Stat SIG) of the American
Educational Research Association. The use of multilevel analyses to
examine effects of groups or contexts on individual outcomes has
burgeoned over the past few decades. Multilevel modeling techniques
allow educational researchers to more appropriately model data that
occur within multiple hierarchies (i.e.- the classroom, the school,
and/or the district). Examples of multilevel research problems
involving schools include establishing trajectories of academic
achievement for children within diverse classrooms or schools or
studying school-level characteristics on the incidence of bullying.
Multilevel models provide an improvement over traditional
single-level approaches to working with clustered or hierarchical
data; however, multilevel data present complex and interesting
methodological challenges for the applied education research
community. In keeping with the pedagogical focus for this book
series, the papers this volume emphasize applications of multilevel
models using educational data, with chapter topics ranging from
basic to advanced. This book represents a comprehensive and
instructional resource text on multilevel modeling for quantitative
researchers who plan to use multilevel techniques in their work, as
well as for professors and students of quantitative methods courses
focusing on multilevel analysis. Through the contributions of
experienced researchers and teachers of multilevel modeling, this
volume provides an accessible and practical treatment of methods
appropriate for use in a first and/or second course in multilevel
analysis. A supporting website links chapter examples to actual
data, creating an opportunity for readers to reinforce their
knowledge through hands-on data analysis. This book serves as a
guide for designing multilevel studies and applying multilevel
modeling techniques in educational and behavioral research, thus
contributing to a better understanding of and solution for the
challenges posed by multilevel systems and data.
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