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Multilevel and Longitudinal Modeling with IBM SPSS (Quantitative Methodology Series), by Ronald H. Heck, Scott L. Thomas, Lynn N. Tabata
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This book demonstrates how to use multilevel and longitudinal modeling techniques available in the IBM SPSS mixed-effects program (MIXED). Annotated screen shots provide readers with a step-by-step understanding of each technique and navigating the program. Readers learn how to set up, run, and interpret a variety of models. Diagnostic tools, data management issues, and related graphics are introduced throughout. Annotated syntax is also available for those who prefer this approach. Extended examples illustrate the logic of model development to show readers the rationale of the research questions and the steps around which the analyses are structured. The data used in the text and syntax examples are available at www.routledge.com/9780415817110.
Highlights of the new edition include:
The book opens with the conceptual and methodological issues associated with multilevel and longitudinal modeling, followed by a discussion of SPSS data management techniques which facilitate working with multilevel, longitudinal, and cross-classified data sets. Chapters 3 and 4 introduce the basics of multilevel modeling: developing a multilevel model, interpreting output, and trouble-shooting common programming and modeling problems. Models for investigating individual and organizational change are presented in chapters 5 and 6, followed by models with multivariate outcomes in chapter 7. Chapter 8 provides an illustration of multilevel models with cross-classified data structures. The book concludes with ways to expand on the various multilevel and longitudinal modeling techniques and issues when conducting multilevel analyses.
Ideal as a supplementary text for graduate courses on multilevel and longitudinal modeling, multivariate statistics, and research design taught in education, psychology, business, and sociology, this book’s practical approach also appeals to researchers in these fields. The book provides an excellent supplement to Heck & Thomas’s An Introduction to Multilevel Modeling Techniques, 2nd Edition; however, it can also be used with any multilevel and/or longitudinal modeling book or as a stand-alone text.
- Sales Rank: #535860 in Books
- Published on: 2013-07-24
- Original language: English
- Number of items: 1
- Dimensions: 10.90" h x 1.00" w x 8.40" l, 2.35 pounds
- Binding: Paperback
- 462 pages
Review
"Ronald Heck and his colleagues have provided academics, graduate students, and practitioners with a resource that few can surpass. This book contains excellent details for users with varying degrees of proficiency in multilevel modelling. It should be on the book shelf of anyone who claims to use this technique." – Timothy Teo, University of Auckland, New Zealand
"This book serves, not only as an introduction to using IBM SPSS for multilevel models, but as a wonderful introduction to multilevel models through empirical example. It is a wonderful resource for an undergraduate or graduate course on multilevel modeling." – Kevin Grimm, University of California, Davis, USA
"This book is ideal for individuals interested in learning about how to analyze different types of multilevel and longitudinal models using the MIXED procedure in IBM SPPS. The book methodically progresses from the simplest of models and designs to the more advanced ones. The presentation of statistical concepts is easy to follow, the data analysis examples are excellent, and the screen shots of the scripts and outputted results are thoroughly and effectively annotated." – George A. Marcoulides, University of California, Riverside, USA
Most helpful customer reviews
10 of 11 people found the following review helpful.
usefull if you are looking for specific instructions
By carmel blank
the book present of procedures using SPSS mixed models. it is very clear and has step-by-step instructions. However, the theoretical part is thin and there are no explanations regarding the statistical model that is in use. for example: if I have a level-2 unit with small number of cases, how does the program handle it? How is the reliability of measurement been measured? etc. These questions are not been answered by the book and therefore it fits to those of you who want to know what to do in order to receive results, but are not interested in the way the program does it.
1 of 1 people found the following review helpful.
When multi-level analysis makes it hard – Modeling with IBM SPSS
By Dr. Gabriel Liberman
Multilevel and Longitudinal Modeling with IBM SPSS by Heck, Thomas and Tabata. Already in the market for couple years, but still makes it easy for those who need results for hierarchical datasets. This book doesn't provide deep theory. Instead, it provides menu-driven and simple programing instructions to produce results. The book is written for everyone in the research community that faces first time the need to control for data structures. New IBM SPSS format has more than one way to model multilevel data and this book covers them all, at least at their basis, and then illustrates alternative result presentation possibilities. It also compares SPSS outputs with other statistical packages to show differences and how to manually calculate moments that SPSS does not produce. I find this book highly useful especially for researchers for whom I provide statistical consulting, when they struggle with understanding the problem of multilevel data-modeling and the way we control for multilevel effects. This book explains results without getting to deep into theory and emphasizes the correct interpretation of the estimates. The book covers the central topics of multilevel analysis such as: what is a multilevel structure of data; how to make first analytical assessment of the multilevel weight; practical instructions for preparing multilevel data for modeling; the two-level regression model and models of higher levels of data; looking across individual change overtime; cross-classification analysis. In each chapter the authors define the problem, the study questions, the restructuring of the data to fit the appropriate model, the modeling procedure and the interpretation of results. Dr. Gabriel Liberman – Data-Graph Statistical Consulting at: [...] .
2 of 2 people found the following review helpful.
Best statistics book I've ever purchased!
By Rick
I'm an entrepreneurship professor that does research on startups. While I'm a subject-matter expert on the startup process, I'm not a statistician. So while I can handle traditional statistical analysis, I delved into the scary world of multi-level longitudinal analysis with a great deal of trepidation and only out of absolute necessity. This book was a god-send, and is in my opinion, the model that all such books should follow. First, it's written in regular English, not indecipherable statistics-speak. It walks readers through many detailed examples, explaining why things are done, what choices should be made, and shows you how to do the analysis, step-by-step in SPSS. Each example is followed by a clear "Interpreting the Output" explanation. Having said that, this is a book on sophisticated statistical analysis, so a careful reading is necessary. Chapters 1 -4 demonstrate the development of multi-level models (with examples) for cross-sectional data. Chapters 5 and beyond does the same with repeated measures (longitudinal) data. My copy now has bookmarks, high-lights and/or written comments on nearly every page. Highly recommend.
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