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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.
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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