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Univariate and multivariate multilevel models are used to understand how to design studies and analyze data in this comprehensive text distinguished by its variety of applications from the educational, behavioral, and social sciences. Basic and advanced models are developed from the multilevel regression (MLM) and latent variable (SEM) traditions within one unified analytic framework for investigating hierarchical data. The authors provide examples using each modeling approach and also explore situations where alternative approaches may be more appropriate, given the research goals. Numerous examples and exercises allow readers to test their understanding of the techniques presented.
Changes to the new edition include:
-The use of Mplus 7.2 for running the analyses including the input and data files at www.routledge.com/9781848725522.
-Expanded discussion of MLM and SEM model-building that outlines the steps taken in the process, the relevant Mplus syntax, and tips on how to evaluate the models.
-Expanded pedagogical program now with chapter objectives, boldfaced key terms, a glossary, and more tables and graphs to help students better understand key concepts and techniques.
-Numerous, varied examples developed throughout which make this book appropriate for use in education, psychology, business, sociology, and the health sciences.
-Expanded coverage of missing data problems in MLM using ML estimation and multiple imputation to provide currently-accepted solutions (Ch. 10).
-New chapter on three-level univariate and multilevel multivariate MLM models provides greater options for investigating more complex theoretical relationships(Ch.4).
-New chapter on MLM and SEM models with categorical outcomes facilitates the specification of multilevel models with observed and latent outcomes (Ch.8).
-New chapter on multilevel and longitudinal mixture models provides readers with options for identifying emergent groups in hierarchical data (Ch.9).
-New chapter on the utilization of sample weights, power analysis, and missing data provides guidance on technical issues of increasing concern for research publication (Ch.10).
Ideal as a text for graduate courses on multilevel, longitudinal, latent variable modeling, multivariate statistics, or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this book’s practical approach also appeals to researchers. Recommended prerequisites are introductory univariate and multivariate statistics.
- Sales Rank: #710903 in Books
- Published on: 2015-03-27
- Released on: 2015-03-23
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x 1.04" w x 6.00" l, .83 pounds
- Binding: Paperback
- 460 pages
Review
"This is a great introductory text with worked examples to guide students and practitioners through analysis and interpretation of multilevel models. The text strikes an effective balance between technical language and applications to demonstrate important concepts." – Grant B. Morgan, Baylor University, USA
"Heck and Thomas provide an introduction to multilevel modeling that is not just comprehensive but also eminently readable. The new edition gives the reader to tackle some of the more recent sophisticated modeling approaches. It is an excellent choice for an instructor looking for a text that helps students to become facile with modeling choices and approaches." – Laura M. Stapleton, University of Maryland, USA
"Developing a basic modeling strategy that researchers can follow to investigate multilevel data structures can be challenging. The authors skillfully present a must-have reference book to get the job done. The easy-to-follow illustrative examples and the extensive software applications are excellent – a masterpiece!" – George A. Marcoulides, University of California, Santa Barbara, USA
"I used the second edition ... in my courses and the improvements for the third edition would be exactly my suggestions. I was especially pleased with the decision to use Mplus. ...The second edition was easy to read and follow―this was the reason that I assigned the book to the students ... in my graduate SEM course. ... I would use the third edition ... in [the same] course." – G. Leonard Burns, Washington State University, USA
"[This] is the only textbook I know of that presents multilevel regression modeling and structural equation modeling as part of a combined framework. ... The revisions … prepare readers to understand both procedures and to conduct both types of analyses. ... The changes make the book a better teaching tool. ... It would be an excellent choice for students who take my multilevel regression modeling course … [and] ... my design of experiments course." – Laura M. O’Dwyer, Boston College, USA
"The proposed changes will certainly make the book a better teaching text. ... The narrative ... provides much needed clarity to a difficult to understand topic. ... I would purchase the book for my personal use and I would (and do) include it on a list of recommended resources on multilevel modelling. ...This book is rather unique in the content it covers and the audience it serves. ... It is meeting a need others are not." – Dick Carpenter, University of Colorado, USA
About the Author
Ronald H. Heck is professor of education at the University of Hawai‘i at Mānoa.
Scott L. Thomas is professor and Dean of the School of Educational Studies at Claremont Graduate University.
Most helpful customer reviews
1 of 1 people found the following review helpful.
The most complex modeling approaches usable for all users
By Dr. Gabriel Liberman
Once again, Dr. Heck and Dr. Thomas break the market by making the most complex modeling approaches usable for all users. No more fancy and costly statistical consulting, simply buy the book and follow the instructions. The authors take the reader through clear and easy examples and show how to build, run and interpret multilevel models. This book follows other books by this team, all of which are designed for anyone who has some knowledge but wants to go further and make the most of the data. Beyond that, Dr. Heck always provides excellent answers to questions I ask as an avid reader of his books. What more can I ask for?
Dr. Gabriel Liberman – Data-Graph Statistical Consulting at: www.data-graph.com .
2 of 2 people found the following review helpful.
There are a number of errors throughout the book (e ...
By Dennis Reidy
There are a number of errors throughout the book (e.g., references from text not in reference list, numbers reported in text don't match numbers in figures). Figures are not well presented and can make it difficult to follow explanation of concepts presented in text. Explanation of concepts is difficult to follow and could be stated in simplified language to improve comprehension. Focus on the practical application of concepts in Mplus is minimal. Although, they provide input syntax for modeling I had hoped they would walk the readers through the syntax and its component parts as well as output.
0 of 0 people found the following review helpful.
Great text book and introduction to multilevel modeling
By Josh
Great text book and introduction to multilevel modeling. You need a basic understanding of SEM for this to be helpful, but it shows you how to use MPlus which is great.
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