Description
This book discusses the current state of multilevel modeling (MLM) research and its applications. It addresses issues such as power, experimental design, and model violations that arise when using MLMs in applied research. The book includes cutting-edge work and statistical innovations in MLM, covering topics such as growth modeling, repeated measures analysis, nonlinear modeling, outlier detection, and meta analysis. It is intended for researchers with advanced statistical training and experience in applying MLMs, particularly in fields such as education, clinical intervention, psychology, and other behavioral sciences. It can also serve as a supplement for an introductory graduate-level course.
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.
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