Multilevel models have become very common in social research, however, there are aspects of these models that are explored only infrequently. Those that rarely make their way into courses and training materials are published articles that appear in academic journals. The author's view is that multilevel modeling offers powerful tools for understanding the multilevel data that social researchers often confront. For example, researchers are often interested in studying outcomes for diverse groups of children in different schools, residents of diverse and different neighborhoods, or individuals or families living in diverse and different countries. Such inherently multilevel data lead to analytic complexities, some of which might be well understood, while others seem to be much less often appreciated. This book offers an accessible tutorial for applied researchers, especially those who see their research having some advocacy based component. The approach of this book, while offering up some equations, is less mathematically rigorous than some of the existing texts, and written with the intent of providing a clear and practically focused guide for the applied researcher who is attempting to carry out better research with diverse populations.
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Andrew Grogan-Kaylor, MA, MSSW, PhD., Sandra K. Danziger Collegiate Professor of Social Work, University of Michigan School of Social Work.
Professor Grogan-Kaylor's research focuses on the associations of parenting behaviors like the use of corporal punishment, or parental expressions of emotional warmth, with child outcomes, examining how these dynamics play out across contexts, neighborhoods, and cultures. Much of his teaching is in interdisciplinary doctoral level statistics courses on advanced quantitative methods.
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