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Filling a gap in the existing literature, this book presents a integrated treatment of latent trait, multilevel, and repeated measurement models in a unified framework that demonstrates the similarities between these models. The author emphasizes and accommodates incomplete data and data of lower measurement levels. He suggests a new estimation strategy along with a comprehensive treatment of methods for obtaining scores on latent traits and random coefficients for individual units, both appearing here for the first time. The text demonstrates the versatility of the methods presented with four extensively worked examples from different disciplines.
Multilevel and Longitudinal Modeling Using Stata, Fourth Edition,
is a complete resource for learning to model data in which
observations are grouped. With comprehensive coverage, researchers
who need to apply multilevel models will find this book to be the
perfect companion. It is also the ideal text for courses in
multilevel modeling because it provides examples from a variety of
disciplines as well as end-of-chapter exercises that allow students
to practice newly learned material. The book comprises two volumes.
Volume I focuses on linear models for continuous outcomes.
Multilevel and Longitudinal Modeling Using Stata, Fourth Edition,
is a complete resource for learning to model data in which
observations are grouped-whether those groups are formed by a
nesting structure, such as children nested in classrooms, or formed
by repeated observations on the same individuals. This text
introduces random-effects models, fixed-effects models,
mixed-effects models, marginal models, dynamic models, and
growth-curve models, all of which account for the grouped nature of
these types of data. As Rabe-Hesketh and Skrondal introduce each
model, they explain when the model is useful, its assumptions, how
to fit and evaluate the model using Stata, and how to interpret the
results. With this comprehensive coverage, researchers who need to
apply multilevel models will find this book to be the perfect
companion. It is also the ideal text for courses in multilevel
modeling because it provides examples from a variety of disciplines
as well as end-of-chapter exercises that allow students to practice
newly learned material. The book comprises two volumes. Volume I
focuses on linear models for continuous outcomes, while volume II
focuses on generalized linear models for binary, ordinal, count,
and other types of outcomes.
Multilevel and Longitudinal Modeling Using Stata, Fourth Edition,
is a complete resource for learning to model data in which
observations are grouped. With comprehensive coverage, researchers
who need to apply multilevel models will find this book to be the
perfect companion. It is also the ideal text for courses in
multilevel modeling because it provides examples from a variety of
disciplines as well as end-of-chapter exercises that allow students
to practice newly learned material. The book comprises two volumes.
Volume II focuses on generalized linear models for binary, ordinal,
count, and other types of outcomes.
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