Practical Multilevel Modeling Using R

Author:   Francis L. Huang
Publisher:   SAGE Publications Inc
ISBN:  

9781071846124


Pages:   256
Publication Date:   01 February 2023
Format:   Paperback
Availability:   To order   Availability explained
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Practical Multilevel Modeling Using R


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Full Product Details

Author:   Francis L. Huang
Publisher:   SAGE Publications Inc
Imprint:   SAGE Publications Inc
Weight:   0.490kg
ISBN:  

9781071846124


ISBN 10:   1071846124
Pages:   256
Publication Date:   01 February 2023
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Active
Availability:   To order   Availability explained
Stock availability from the supplier is unknown. We will order it for you and ship this item to you once it is received by us.

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Reviews

The book describes multilevel modeling well by minimizing mathematics, utilizing the R software, and moving from a simple case to more complex cases. The author includes the syntax and output so that readers can test it themselves, and visual examples are given. Doctoral students in education and psychology will benefit from this book. -- Muhammet Mustafa Alpaslan A major strength of this book is its accessibility. Huang effortlessly bridges the divide between the sometimes-abstruse literature on advanced statistics and the needs of applied researchers who lack extensive quantitative training. The result is an approachable text that covers all the basics, but also does not shy away from important advanced topics such as diagnostics, detecting and handling heteroscedasticity, and missing data handling methods. This book would make not only a useful guide to the application of multilevel modeling, but could also serve as an excellent companion text for a course on multilevel modeling. -- Kristopher J. Preacher This book is an excellent book for a graduate level multilevel modeling course that utilizes R; it perfectly combines the depth and breadth on this topic. -- Wei Wang


The book describes multilevel modeling well by minimizing mathematics, utilizing the R software, and moving from a simple case to more complex cases. The author includes the syntax and output so that readers can test it themselves, and visual examples are given. Doctoral students in education and psychology will benefit from this book. -- Muhammet Mustafa Alpaslan Practical examples and simple solutions for complex multilevel analysis tasks make this book a great reference source for students and researchers alike. -- Hakan Islamoglu A major strength of this book is its accessibility. Huang effortlessly bridges the divide between the sometimes-abstruse literature on advanced statistics and the needs of applied researchers who lack extensive quantitative training. The result is an approachable text that covers all the basics, but also does not shy away from important advanced topics such as diagnostics, detecting and handling heteroscedasticity, and missing data handling methods. This book would make not only a useful guide to the application of multilevel modeling, but could also serve as an excellent companion text for a course on multilevel modeling. -- Kristopher J. Preacher This book is an excellent book for a graduate level multilevel modeling course that utilizes R; it perfectly combines the depth and breadth on this topic. -- Wei Wang


Author Information

Francis Huang, Ph.D. is an Associate Professor at the University of Missouri (MU) in the Statistics, Measurement, and Evaluation in Education program in the Department of Educational, School, and Counseling Psychology of the College of Education. He teaches courses on multilevel modeling, program evaluation, and data management and is the co-director of the methodology branch of the Missouri Prevention Science Institute. Dr. Huang’s research has been funded by federal agencies such as the U.S. Department of Education and the National Institute of Justice. His research focuses on both methodological (e.g., analysis of clustered data) and substantive (e.g., school climate, bullying, disparities in disciplinary sanctions) areas of interest. His work has been cited in outlets such as the New York Times, the Washington Post, and National Public Radio (among others). He has published in journals such as the Journal of Educational and Behavioral Statistics, Behavior Research Methods, and Educational Researcher. Prior to joining MU, he was a Senior Scientist at the University of Virginia and has worked at the American Institutes for Research, providing technical expertise on survey methods and the analysis of large-scale secondary datasets. He has worked as a management consultant and a high school teacher. He has an MA from Teachers College, Columbia University and a PhD from the University of Virginia. He is a father of two and married to his best friend. Francis does not take himself too seriously, plays the guitar, and dreams of being in a jazz trio in his retirement.

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