This book illustrates the current work of leading multilevel
modeling (MLM) researchers from around the world.
The book's goal is to critically examine the real problems that
occur when trying to use MLMs in applied research, such as power,
experimental design, and model violations. This presentation of
cutting-edge work and statistical innovations in multilevel
modeling includes topics such as growth modeling, repeated measures
analysis, nonlinear modeling, outlier detection, and meta
analysis.
This volume will be beneficial for researchers with advanced
statistical training and extensive experience in applying
multilevel models, especially in the areas of education; clinical
intervention; social, developmental and health psychology, and
other behavioral sciences; or as a supplement for an introductory
graduate-level course.
General
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