Linear Models Haase171 Methods of Randomization in Experimental Design Alferes
172 Heteroskedasticity in Regression Kaufman
173 An Introduction to Exponential Random Graph Modeling Harris
174 Introduction to Time Series Analysis Pickup
175 Factorial Survey Experiments Auspurg/Hinz
176 Introduction to Power Analysis: Two-Group Studies Hedberg
177 Linear Regression: A Mathematical Introduction Gujarati
178 Propensity Score Methods and Applications Bai/Clark
179 Multilevel Structural Equation Modeling Silva/Bosancianu/Littvay
180 Gathering Social Network Data Adams
181 Generalized Linear Models for Bounded and Limited Quantitative Variables Smithson/Shou
182 Exploratory Factor Analysis Finch
183 Multidimensional Item Response Theory Bonifay
184 Argument-Based Validation in Testing and Assessment Chapelle
Sara Miller McCune founded SAGE Publishing in 1965 to support the dissemination of usable knowledge and educate a global community. SAGE publishes more than 1000 journals and over 800 new books each year, spanning a wide range of subject areas. Our growing selection of library products includes archives, data, case studies and video. SAGE remains majority owned by our founder and after her lifetime will become owned by a charitable trust that secures the company’s continued independence.
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MULTILEVEL MODELING
Second Edition
Douglas A. Luke
Washington University in St. Louis
Copyright © 2020 by SAGE Publications, Inc.
All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher.
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Praise for The Second Edition
Because of the author’s pedagogically masterful presentation of multi-level modeling, the otherwise challenging journey to this topic now becomes not only smooth but also enjoyable.
—Lin Ding, Ohio State University
The book offers insights and explanations from which both newcomers and seasoned experts can find benefit.
—Timothy Ford, Ohio University
This is a thorough and accessible introduction to multilevel models. Through extensive examples, the author expertly guides the reader through the material addressing interpretation, graphical presentation, and diagnostics along the way.
—Jennifer Hayes Clark, University of Houston
The Second Edition is even better than the first. The models presented are closely linked to an extended example that students can readily identify with.
—Richard R. Sudweeks, Brigham Young University
About the Author
Douglas A. Lukeis Professor and Director of the Center for Public Health Systems Science at the Brown School at Washington University in St. Louis. Dr. Luke is a leading researcher in the areas of public health policy, implementation science, and systems science. Most of the work that Dr. Luke directs at the Center focuses on the evaluation, dissemination, and implementation of evidence-based public health policies. During the past decade, Dr. Luke has worked on applying systems science methods to important public health problems, especially social network analysis. He has published two systems science review papers in the Annual Review of Public Health, and the first study to employ new statistical network modeling techniques on public health data was published in the American Journal of Public Health in 2010. He was also a member of a National Academy of Sciences panel that produced a recent report, “Assessing the Use of Agent-Based Models for Tobacco Regulation,” which provided the FDA and other public health scientists with guidance on how best to use computational models to inform tobacco control regulation and policy. Dr. Luke directs the doctoral progam in Public Health Sciences at the Brown School, where he also teaches doctoral courses in multilevel and longitudinal modeling, social network
