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Linear Mixed Models
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Description
Highly recommended by JASA, Technometrics, and
other leading statistical journals, the first two
editions of this bestseller showed how to easily
perform complex linear mixed model (LMM) analyses
via a variety of software programs. Linear Mixed
Models A Practical Guide Using Statistical
Software, Third Edition continues to lead readers
step-by-step through the process of fitting LMMs.
The third edition provides a comprehensive update
of the available tools for fitting linear
mixed-effects models in the newest versions of
SAS, SPSS, R, Stata, and HLM. All examples have
been updated, with a focus on new tools for
visualization of results and interpretation. New
conceptual and theoretical developments in
mixed-effects modeling have been included, and
there is a new chapter on power analysis for
mixed- effects models.Features8226Deicates an
entire chapter to the key theories
underlying LMMs for clustered, longitudinal, and
repeated measures data8226Prvides
descriptions, explanations, and examples of
software code necessary to fit LMMs in SAS, SPSS,
R, Stata, and HLM8226Cotains detailed tables of
estimates and results, allowing for
easy comparisons across software
procedures8226Prsents step-by-step analyses of
real-world data sets that arise from a variety of
research settings and study designs,
including hypothesis testing, interpretation of
results, and model diagnostics8226Inegrates
software code in each chapter to compare the
relative advantages and disadvantages of
each package8226Suplemented by a website with
software code, datasets, additional documents,
and updatesIdeal for anyone who uses software for
statistical modeling, this book eliminates the
need to read multiple software-specific texts by
covering the most
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popular software programs for fitting LMMs in one
handy guide. The authors illustrate the models
and methods through real-world examples that
enable comparisons of model-fitting options and
results across the software procedures.